Paytient is on a mission to help people live better lives by improving their ability to better access and afford care

Paytient

Medical Software Testing 101: Advice to Consider for Upgrading Patient Experiences 

"The most effective debugging tool is still careful thought, coupled with judiciously placed print statements." -- Brian Kernighan. Cutting a patient open and using print for debugging used to be the best way to diagnose problems. If you still advocate either one of those as the superior approach to troubleshooting, then you're either facing a very niche problem or need to update your knowledge. This is a frequent occurrence, e.g., this recent tweet: This specific tweet got to the HN front page, and people chimed in with that usual repetitive nonsense. No, it’s not the best way for the vast majority of developers. It should be discouraged just as surgery should be avoided when possible. Fixating on print debugging is a form of a mental block; debugging isn’t just stepping over code. It requires a completely new way of thinking about issue resolution. A way that is far superior to merely printing a few lines. Before I continue, my bias is obvious. I and I . This is a pet peeve of mine. , wrote a book about debugging blog about it a lot I want to start with the exception to the rule, though: when do we need to print something... Logging is NOT Print Debugging! One of the most important debugging tools in our arsenal is a logger, but it is not the same as print debugging in any way: Logger Print Permanence of output Permanent Ephemeral Permanence in code Permanent Should be removed Globally Toggleable Yes No Intention Added as part of design Added ad-hoc A log is something we add with forethought. We want to keep the log for future bugs and might even want to expose it to the users. We can control its verbosity often at the module level and can usually disable it entirely. It’s permanent in code and usually writes to a permanent file we can review at our leisure. Print debugging is code we add to locate a temporary problem. If such a problem has the potential of recurring, then a log would typically make more sense in the long run. This is true for almost every type of system. We see developers adding print statements and removing them constantly instead of creating a simple log to track frequent problems. There are special cases where print debuggings makes some sense, in mission critical embedded systems a log might be impractical in terms of device constraints. Debuggers are awful in those environments, and print debugging is a simple hack. Debugging system-level tools like a kernel, compiler, debugger, or JIT can be difficult with a debugger. Logging might not make sense in all of these cases, e.g., I don’t want my JIT to print every bytecode it’s processing and the metadata involved. Those are the exceptions, not the rules. Very few of us write such tools. I do, and even then, it’s a fraction of my work. For example, when working at Lightrun, I was working on a production debugger. Debugging the agent code that’s connected to the executable was one of the hardest things to do. A mix of C++ and JVM code that’s connected to a completely separate binary... Print debugging of that portion was simpler, and even then, we tried to aim towards logging. However, the visual aspects of the debugger within the server backend and the IDE were perfect targets for the debugger. Why Debug? There are three reasons to use a debugger instead of printouts or even logs: Features - modern debuggers can provide spectacular capabilities that are unfamiliar to many developers. Sadly, there are very few debugging courses in academia since it’s a subject that’s hard to test. Low overhead - in the past, running with the debugger meant slow execution and a lot of overhead. This is no longer true. Many of us use the debug action when launching an application instead of running, and there’s no noticeable overhead for most applications. When there is overhead, some debuggers provide means to improve performance by disabling some features. Library code - a debugger can step into a library or framework and track the bug there. Doing this with print debugging will require compiling code that you might not want to deal with. I dug into the features I mentioned in my book and series on debugging (linked above), but let’s pick a few fantastic capabilities of the debugger that I wrote about in the past. For the sake of positive dialog, here are some of my top features of modern debuggers. Tracepoints Whenever someone opens the print debugging discussion, all I hear is, “I don’t know about tracepoints”. They aren’t a new feature in debuggers, yet so few are aware of them. A tracepoint is a breakpoint that doesn’t stop. It just keeps running. Instead of stopping, you can do other things at that point, such as print to the console. This is similar to print debugging, only it doesn’t suffer from many of the drawbacks: no runtime overhead, no accidental commit to the code base, no need to restart the application when changing it, etc. https://www.youtube.com/watch?v=eXRqKqSp7x0&embedable=true Grouping and Naming The previous video/post included a discussion of grouping and naming. This lets us group tracepoints together, disable them as a group, etc. This might seem like a minor feature until you start thinking about the process of print debugging. We slowly go through the code, adding a print and restarting. Then suddenly, we need to go back, or if a call comes in and we need to debug something else... When we package the tracepoints and breakpoints into a group, we can set aside a debugging session, much like we set aside a branch in version control. It makes it much easier to preserve our train of thought and jump right back to the applicable lines of code. Object Marking When asked about my favorite debugging feature I’m always conflicted, ... It seems like a simple thing; we can mark an object, and it gets saved with a specific name. Object Marking is one of my top two features However, this is a powerful and important feature. I used to write down the pointers to objects or memory areas while debugging. This is valuable as sometimes an area of memory would look the same but would have a different address, or it might be hard to track objects with everything going on. Object Marking allows us to save a global reference to an object and use it in conditional breakpoints or for visual comparison. https://www.youtube.com/watch?v=DGjVVKCNosM&embedable=true Renderers My other favorite feature is ; it lets us define how elements look in the debugger watch area. Imagine you have a sophisticated object hierarchy but rarely need that information... A renderer lets you customize the way IntelliJ/IDEA presents the object to you. the renderer https://www.youtube.com/watch?v=oaUf8KXHsd0&embedable=true Tracking New Instances One of the often overlooked capabilities of the debugger is . A Java debugger can show you a searchable set of all object instances in heap, that is a fantastic capability that can expose unintuitive behavior But it can go further, it can track new allocations of an object and provide you with the stack to the applicable object allocation. memory tracking https://www.youtube.com/watch?v=dFOFOEg2W4k&embedable=true Tip of the Iceberg I wrote a lot about debugging, so there’s no point in repeating all of it in this post. If you’re a person who feels more comfortable using print debugging, then ask yourself this: why? Don’t hide behind an out-of-date Brian Kernighan quote. Things change. Are you working in one of the edge cases where print debugging is the only option? Are you treating logging as print debugging or vice versa? Or is it just that print debugging was how your team always worked, and it stuck in place? If it’s one of those, then it might be time to re-evaluate the current state of debuggers. Also published . here

Stop Cutting Your Patients Open: Rethinking Print for Debugging 

Efficient medical inventory management is crucial for healthcare supply chains, making up more than . Unlike conventional logistics, healthcare operations ensure the timely delivery of quality medical care. 37% of total patient care costs Creating customized inventory software for hospitals makes the process even more efficient, solving procurement challenges and improving patient outcomes. In this article, I will outline 5 important practical steps to upgrade inventory management for hospitals and medical facilities, and provide insights into its significance for business growth. Understanding Healthcare Inventory Management In healthcare, keeping track of supplies creates the backbone for smooth operations and internal medical facility processes and workflows. It is especially important for large hospital systems , each with its own inventories and workflows. managing multiple healthcare facilities Typically, the challenges healthcare providers aim to solve with efficient inventory management include: consistent and timely restocking; excessive use of supplies; limited data visibility; manual data entry; outdated healthcare workflows; difficult communication with suppliers. Tackling the challenges requires healthcare professionals to invest in smarter inventory management as a way to improve the quality of medical care and patient outcomes. Let’s take a closer look at necessary to improve the way hospitals and medical facilities handle inventory. 5 crucial steps Getting Instant Insights Into Healthcare Storage Limited knowledge about available medicines and equipment can cause significant problems with managing inventory. As a result, important items may either not be available in emergencies or expire before they need to be used. As a result, healthcare facilities may face financial losses and damage to their reputation. To address this issue, healthcare facilities should think of establishing into medical inventories. This way, they can get timely . real-time visibility updates on consumption and expiration dates and enable consistent and professional medical care Here are a few essential features solutions like this usually have: offer a categorized detailed view of medicines and medical equipment. Inventory lists: provides an integrated view of stock supplies across departments, storerooms, and warehouses. Stock overview: allows procurement specialists to monitor medicine and medical supplies consumption to refill the stock promptly. Usage tracking: let inventory managers receive real-time updates on items low in stock or nearing expiration. Customized alerts: Leveraging a Data-Driven Strategy for Consumption and Restocking Continuous monitoring of inventory lets healthcare organizations assess the utilization of medical supplies and make procurement decisions based on statistical data. Depending on the goals of a medical facility, the collected data can assist with certain issues such as or help build an advanced demand forecasting system. , excessive utilization, cost distribution management For further improvement of healthcare inventory management systems, I also recommend implementing and reports. They would be a reliable data source for healthcare executives, lower maintenance costs, and optimize procurement processes. custom dashboards provide a comprehensive overview of the quantity of items used over a specified time period. Analytics on quantity changes help monitor critical item quantities, determine optimal restock frequency and order amounts, and set minimum inventory levels. Reports on low-in-stock items offer a perspective on costs associated with inventory items and utilization. This way, business executives can compare planned versus actual spending and facilitate the planning of future inventory budgets. Cost distribution reports shows a list of activities within specific warehouses, facilities, or departments. It helps see and track typical actions performed by inventory workers and nursing staff over a specific time period, resulting in improved operational and workflow optimization. Activity monitoring Enabling Simplified Communication With Suppliers Order management is a crucial element in the success of the healthcare supply chain. However, many current inventory management software options for hospitals lack the features needed to automate order placement and tracking. Even with bulk purchasing contracts common among large healthcare providers, procurement executives still struggle to ensure timely supply delivery. They face different challenges, like finding the right distributor, confirming product availability, negotiating delivery times, placing orders, and monitoring fulfillment. If issues arise, communication with vendors, re-ordering, and adjusting prices can take hours. facilitates communication between inventory specialists and suppliers within healthcare inventory management software. A built-in module with order management features includes details about current vendors and allows for adding new ones. Smart filters enable inventory managers to quickly assess the best options by checking item availability in specific regions or desired delivery terms. A digital list of vendors lets procurement staff easily access information about each order, view expected delivery dates, adjust amounts, and make changes. Checking order details provides a real-time view of all orders, whether they are saved as drafts, confirmed by suppliers, or fulfilled. Monitoring order status allows inventory managers to access order data and set minimum inventory levels that will automatically initiate orders for items before they appear low in stock. Automated order placement Streamlining Workflows Within Healthcare Facilities Similar to other traditional industries, healthcare is undergoing a digital transformation. Among the different existing challenges, outdated processes, and low digital dexterity play a key role in technology adoption. Intelligent automation replaces time-consuming manual processes, decreases businesses’ operational costs, and , improving patient outcomes. saves hospital staff’s time for quality medical care and scanning them with a mobile camera or other device automatically updates information about medical supplies or requests a restock without the need for manual input of numbers and names. Implementing barcodes and RFID tags between hospital staff and administrative teams improves access to inventory data, facilitates requests for necessary medications, and provides timely updates on available healthcare supplies in stock. Simplifying communication minimizes human errors, standardizes data formats, and makes essential inventory data available for executives and stakeholders all the time. Transitioning away from spreadsheets and paper records Ensuring a Consistent Inventory Process To deliver quality patient care, healthcare organizations often solve individual issues in conjunction with healthcare supply chains. However, the key to overcoming healthcare inventory management challenges is to inventory management establish integrity in inventory processes and workflows. To create a central point of connection for all the facilities, departments, and employees, consider implementing the following solutions. into inventory management transformation to give teams access to information whenever needed, facilitate online collaboration, and streamline procurement processes. Incorporate cloud enablement functionality and utilize reporting and analytics tools to save teams' time, keep them informed about the real situation in medical storerooms, prevent critical stockout situations, and reduce utilization costs. Integrate order management designed for healthcare facilities to convert records into digital formats, add tools for online collaboration, and help employees overcome digital friction. Choose custom software Wrapping Up Effective inventory management in healthcare is vital for providing excellent medical services. When hospital staff and procurement specialists are tied up with manual tasks like updating medication information and placing orders, patient safety is at risk. Adopting a comprehensive approach to inventory tracking and automating routine facility workflows is the solution to improving any healthcare business. By implementing these measures, organizations can not only enhance operational efficiency but also ensure the well-being of their patients.

Effective Healthcare Inventory Management: 5 Elements for Excellent Patient Outcomes

Over the past few decades, there have been significant increases in research and development efforts toward the cure of terminal diseases. The healthcare space has seen significant development as new technologies have come to take the place of old ones, and this has led to several impressive breakthroughs in the diagnosis and treatment of diseases across the board. For this very reason, many are now leaning heavily on the possible use of blockchain technology for improved healthcare research. Blockchain has quickly emerged as one of the most innovative technologies in the world, with applications across multiple fields - including business, governance, and even education. However, while there is no doubt that blockchain will be one of the pivotal technologies of tomorrow’s internet landscape, its application for healthcare innovation has been somewhat stifled. Up until this moment, most of blockchain’s application has been focused on financial innovation. Whether it is the backing of cryptocurrencies or the foundation of decentralized finance (DeFi), most blockchain developers appear more focused on using innovative technology to solve the biggest issues we have with money. Still, blockchain is functional for more than this - especially as the world continues to look for innovations in the healthcare space. And, now that Amrit A.G. is getting ready for its massive rollout of the Amrit Ecosystem, there is a distinct possibility that blockchain could finally help to deliver high-quality research geared towards solving incurable and terminal diseases. Amrit A.G., through the Amrit ecosystem, is looking to bring one of the biggest benefits of blockchain technology to the medical space - improving trust in the research process and enabling decentralized science. The platform was built on the belief that data is indeed life, and that the world needs high-quality, accurate data as everyone now focuses on the treatment of cancer and other incurable disorders. It also ensures that the true benefit of data licensing and research flows back to the patients with complete transparency. Based in Switzerland, Amrit A.G. was built on the premise that researchers in the oncology field will continue to need high-quality data. In this interview, we spoke to the company’s Co-CEO and Co-Founder, Ashwin Rathod about its innovation. 1: What was the primary reason you saw with oncology that made you want to launch the Amrit ecosystem? When my close friend’s dad was diagnosed with oral cancer, we were stranded and helpless with no access to accurate, unbiased information. All across the internet, wherever we searched for the information was biased, often ripe with misinformation and ad-driven search results or driving propagandas. We lost him to cancer because we were delayed in the treatment and finding the right expert and site for his treatment. This happens to millions of people across the world especially in the developing countries where access to healthcare and life-saving information is not easy. I took a lead to change this situation and hence co-founded Amrit A.G. (previously OncoCoin A.G.) to create an ecosystem focused on patient empowerment and giving them total control over their data. Thanks to blockchain and cryptography we are able to create an ecosystem that uses encryption and anonymity as the basis of trust thereby enabling the patients to drive the research ground up. 2: What inefficiencies are plaguing the research process right now? For decades humanity has been plagued with the inefficiencies in drug discovery and bringing out treatments to the market, especially for incurable and terminal diseases like cancer, Alzheimer’s, Parkinson’s disease, etc… Every year $200B is spent by big pharma on research and development and yet only 50 drugs get an approval every year. One of the major reasons is the disconnect between patients and researchers mainly due to the lack of transparency involving use (or misuse) of patient’s healthcare data. As a result, we have precious healthcare data residing in silos which cannot be utilized for the research. We believe blockchain and Decentralized ID-based solutions like the Amrit Ecosystem could hold the key to break this gap of trust. 3: Are there plans to use the Amrit ecosystem in partnership with hospitals and research facilities in the future? Yes, we are already working with hospitals, labs, and other data aggregators in order to ensure that the data can be used for specific research purposes without the patients being identified and also with their consent. The partner Apps launched on Amrit Ecosystem and various healthcare stakeholders can provide their services and host research projects on the ecosystem which helps the patient community to avail these life-saving services from the partners and apps in the ecosystem. I believe that the way forward would be to have distributed web nodes and decentralized ID-based access to researchers with patient consent at the core of the solution. Currently, various healthcare partners in Asia and Europe and apps from across the world are rapidly growing fueled by a fluid integration of the service layer and vice-versa. Our vision is to bring all the healthcare stakeholders as a collective where we want to slowly pass on the decision-making through a robust consensus mechanism where every stakeholder can contribute to the growth of the ecosystem and also patients could stake their RWD to catapult the success of a project and also benefit from the value created thereby. 4: Is cancer research the endgame? Or do you see Amrit expanding to other forms of medical research? Oncology is surely a starting point however we already have scaled up to Neurology related disorders and in the near future, we are targeting other therapeutic areas (TA) aimed towards alternative therapies, preventive care, and precision medicine. Having said that, our goal is to have comprehensive coverage of services and projects from every stakeholder in healthcare. We have been able to showcase enormous scalability across dimensions like TA, geographies, services, multi-modal healthcare data types, and much more. This is possible through our patented AI algorithms and robust and highly scalable service layers. As of today, we have more than 67 granted patents and 125+ filed patents which I believe is a stupendous achievement for a startup like us. 5: How have you navigated the medical field in terms of regulations surrounding the application of blockchain technology? We are at the forefront of creating something unique that has never been done before and we want a sustainable and inclusive path forward. Speaking of the regulations around blockchain and cryptocurrencies, we are of the opinion that these regulations are still maturing and most of the geographies are trying to formulate holistic policies which is a welcome step. The pace at which blockchain and cryptocurrencies have evolved in just the past couple of years is truly astounding and the innovations that appear every day are revolutionizing multiple industry sectors, especially the healthcare, finance, communications, and internet as a whole. This also poses a challenge for the regulators to ensure that citizens are not adversely affected by misleading information. While most of the governments are aligned with the benefits of the blockchain technology and cryptography, some are also cautious of the implications of absolute privacy, money laundering, terror financing, and other illicit activities including financial scams. Compliance with local and global regulations is paramount to our expansion strategy. To that effect, we employ only the best of the legal teams specialized in various aspects ranging from KYC, AML checks, data privacy, security, anonymity and sovereignty, patient data handling and storage, laws of doing business, regional marketing and communication guidelines, and much more. We are also ISO27001 certified, HIPAA compliant and use end-to-end AES256 bit encryption which is also recommended by the National Security Advisor(NSA) to the US Govt.

Breaking The Loop Of Trust While Dealing With Real-World-Data Between The Patients And Researchers

First Employee: My Journey From Solopreneur to Entrepreneur

Gianluca Sacco Unveils VALR's Grand Slam Trading Incentives: A New Era in Crypto Futures

Gianluca Sacco VALR এর গ্র্যান্ড স্ল্যাম ট্রেডিং ইনসেনটিভ উন্মোচন করেছে: ক্রিপ্টো ফিউচারে একটি নতুন যুগ

Gianluca Sacco stellt VALRs Grand-Slam-Handelsanreize vor: Eine neue Ära bei Krypto-Futures

Gianluca Sacco presenta los incentivos comerciales Grand Slam de VALR: una nueva era en los futuros criptográficos

Gianluca Sacco dévoile les incitations commerciales du Grand Chelem de VALR : une nouvelle ère dans les contrats à terme sur cryptographie

जियानलुका सैको ने VALR के ग्रैंड स्लैम ट्रेडिंग प्रोत्साहनों का खुलासा किया: क्रिप्टो फ्यूचर्स में एक नया युग

ジャンルカ・サッコがVALRのグランドスラム取引インセンティブを発表: 暗号通貨先物取引の新時代

Gianluca Sacco, VALR의 그랜드 슬램 트레이딩 인센티브 공개: 암호화폐 선물의 새로운 시대

Gianluca Sacco revela os incentivos de negociação do Grand Slam da VALR: uma nova era em futuros criptográficos

Джанлука Сакко представляет торговые стимулы Большого шлема VALR: новая эра в криптофьючерсах

Gianluca Sacco, VALR'ın Grand Slam Ticaret Teşviklerini Açıkladı: Kripto Vadeli İşlemlerinde Yeni Bir Dönem

Gianluca Sacco tiết lộ các ưu đãi giao dịch Grand Slam của VALR: Kỷ nguyên mới trong hợp đồng tương lai tiền điện tử

Gianluca Sacco 揭晓 VALR 大满贯交易激励措施：加密货币期货的新时代

Software developers rarely design the most aesthetically pleasing software. These principles can help you and other developers change this narrative. Keep it simple. Simplicity is a principle to follow in design. Overcomplicating your design won’t make it better in most cases. Beautiful designs can be created from the simplest ideas. Sometimes, good ideas become useless due to over-complication. People like beautiful things that aren’t complicated. It does not matter how good your software is if the users cannot find their way around it. A simple and beautiful design is more beneficial than a complicated design. Keep things simple and functional. Your clientele will thank you for this. Avoid Reinventing the Wheel Reinventing the wheel is re-creating something already created, tested, and proven effective. It harms overall development and often leads to unnecessary complexity. It's better to use existing and proven solutions. An underrated tactic is gaining inspiration from another creation and making it your own with your twist. We have used this principle to enhance the aesthetics of Goleko. We took inspiration from MacOS, customizing our buttons and features using it as a guide. We plan to take some inspiration from Windows and incorporate it into the design, creating a fresh and unique outlook that is Goleko. We’ll make designs similar to Windows and MacOS, allowing users to experience a theme familiar to their machine. It is okay to steal designs and add your flare to them. You can steal such designs from other websites or get them from themes. Our designs are simple and functional, conforming to design best practices. We don’t do too much. We improve where necessary to improve user experience (UX), but we do not try to change what has been proven to be efficient. Avoid Tunnel Vision. It’s not rare for designers to get engulfed in their designs. Tunnel vision makes it hard for designers to see the holes or weaknesses in their design. The result is a design that’s pleasing for them but not for their target clientele. Focusing on completion instead of other effects is detrimental to your design. Take time to determine what works well for your design and what your users want. Design something that incorporates the two. This will help you avoid tunnel vision, allowing you to create something that works well for users. Consistency Over Fanciness Creating a fancy product is a good thing, and it’s highly recommended. This does not mean you ignore its consistency. Clients prefer a product that remains consistent in delivering what they need. Design a product that works and delivers as advertised. You can incorporate consistent paddings and margins into this as well. It helps to make a site appear clean and easily readable. This also follows the law of continuity. This law states that we tend to see continuous patterns and lines. These create a sense of flow and hierarchy in designs by using continuous lines or color gradients, creating a sense of movement. These guide the user's eye toward important information. Such simple solutions promote consistency for your products, making them viable and usable by your clients. Proportions Excellent designs have elements of different sizes that fit nicely together to create coherent proportions. Here is an example: Websites can display different content types, such as articles, videos, and images. Highlight the most crucial content and guide the user's eye toward it. A good example specific for me is making the article section livelier than the other sections. I do this when articles are the most pivotal content on a website. Implement different proportions to create emphasis. You can use smaller proportions for less critical content, such as images or videos. This creates a hierarchy of importance and guides the user's eye to the most crucial elements of the website. Color Adherence The best designers understand how to combine different colors that complement each other. This mere statement sounds simple, but is a science. Flatuicolors has numerous color palettes showcasing different colors that accentuate and complement each other. A successful product is both functional and visually pleasing. Picking the best color scheme goes a long way in making your product beautiful and enjoyable to use by everyone. Colors brighten everything, and pairing them with their ideal partners is the first step to creating a masterpiece. Conclusion Software developers focus on designing a product that works well. Designing the aesthetics isn’t a concern for them. This makes it easy for them to create software that’s not easy on the eye or welcoming. These principles can help bridge this gap between development and design. It shouldn’t be rare for a developer to design a pleasing product. This piece can help start this trend. FAQs Are software developers creative?Contrary to popular belief, software developers are creative beasts. Writing good code requires logic as you need to get things done properly, but you also need the creativity to make a good solution. Software developers combine these two skills with excellent drive and efficiency to create software that solves issues and improves the lives of people. Can you learn to build beautiful software?Yes, you can. You practice your coding, learn from your mistakes, and improve your application - this is the same for design. It takes time to develop these skills and to perfect them. Be patient with yourself and work on your skills. It helps to note your lessons and improve upon your mistakes. Doing this will help you build beautiful and elegant software. Is software development an artistic field?Yes, it is. It incorporates the style of a savant with the imagination of a visionary to create software that works as expected. It's like interacting with a wine connoisseur. They take in every part of the process, analyze every detail, and put it together to create the best software for people to use. They put effort into the user interface, the user experience, and functionality. The outcome is elegant software that works well and gives the users what they want. Is building software a hard thing to do?Yes, it is. It takes a lot of time and effort to build elegant software. Software developers hone their skills and practice their coding to create elegant software. They learn from their mistakes and implement their skills to create better software to help people in society. They learn to use different coding tools and methods to create elegant software. They give everything to make the world a better place one code at a time. Are software engineers creative?Software engineers are creative. They work well and remain on topic. They have valuable insight they use to enhance their ideas to improve code and applications. They use their creativity to implement visual and structural changes to the programs. They make software that benefits the users and helps the community at large. Is creativity essential to software development?Yes, it is. The software developers are like other professionals. They take in feedback, analyze it, and creatively formulate solutions. Their decision-making and dedication make them excellent workers with cool insights. They generally follow a routine but have complex processes to solve team and community problems. They are creative and effective in their work. Are there services that need software developers?Yes, there are. Software developers are needed in web development, app development, and specialized coding. They are needed in marketing, programming, and various projects. A software developer's skills are diverse and needed in almost every industry. For these and more thoughts, guides and insights visit my blog at martinbaun.com Software developers rarely design the most aesthetically pleasing software. These principles can help you and other developers change this narrative. Keep it simple. Simplicity is a principle to follow in design. Overcomplicating your design won’t make it better in most cases. Beautiful designs can be created from the simplest ideas. Sometimes, good ideas become useless due to over-complication. People like beautiful things that aren’t complicated. It does not matter how good your software is if the users cannot find their way around it. A simple and beautiful design is more beneficial than a complicated design. Keep things simple and functional. Your clientele will thank you for this. Avoid Reinventing the Wheel Reinventing the wheel is re-creating something already created, tested, and proven effective. It harms overall development and often leads to unnecessary complexity. It's better to use existing and proven solutions. An underrated tactic is gaining inspiration from another creation and making it your own with your twist. We have used this principle to enhance the aesthetics of Goleko. We took inspiration from MacOS, customizing our buttons and features using it as a guide. We plan to take some inspiration from Windows and incorporate it into the design, creating a fresh and unique outlook that is Goleko. We’ll make designs similar to Windows and MacOS, allowing users to experience a theme familiar to their machine. It is okay to steal designs and add your flare to them. You can steal such designs from other websites or get them from themes. Our designs are simple and functional, conforming to design best practices. We don’t do too much. We improve where necessary to improve user experience (UX), but we do not try to change what has been proven to be efficient. Avoid Tunnel Vision. It’s not rare for designers to get engulfed in their designs. Tunnel vision makes it hard for designers to see the holes or weaknesses in their design. The result is a design that’s pleasing for them but not for their target clientele. Focusing on completion instead of other effects is detrimental to your design. Take time to determine what works well for your design and what your users want. Design something that incorporates the two. This will help you avoid tunnel vision, allowing you to create something that works well for users. Consistency Over Fanciness Creating a fancy product is a good thing, and it’s highly recommended. This does not mean you ignore its consistency. Clients prefer a product that remains consistent in delivering what they need. Design a product that works and delivers as advertised. You can incorporate consistent paddings and margins into this as well. It helps to make a site appear clean and easily readable. This also follows the law of continuity. This law states that we tend to see continuous patterns and lines. These create a sense of flow and hierarchy in designs by using continuous lines or color gradients, creating a sense of movement. These guide the user's eye toward important information. Such simple solutions promote consistency for your products, making them viable and usable by your clients. Proportions Excellent designs have elements of different sizes that fit nicely together to create coherent proportions. Here is an example: Websites can display different content types, such as articles, videos, and images. Highlight the most crucial content and guide the user's eye toward it. A good example specific for me is making the article section livelier than the other sections. I do this when articles are the most pivotal content on a website. Implement different proportions to create emphasis. You can use smaller proportions for less critical content, such as images or videos. This creates a hierarchy of importance and guides the user's eye to the most crucial elements of the website. Color Adherence The best designers understand how to combine different colors that complement each other. This mere statement sounds simple, but is a science. Flatuicolors has numerous color palettes showcasing different colors that accentuate and complement each other. A successful product is both functional and visually pleasing. Picking the best color scheme goes a long way in making your product beautiful and enjoyable to use by everyone. Colors brighten everything, and pairing them with their ideal partners is the first step to creating a masterpiece. Conclusion Software developers focus on designing a product that works well. Designing the aesthetics isn’t a concern for them. This makes it easy for them to create software that’s not easy on the eye or welcoming. These principles can help bridge this gap between development and design. It shouldn’t be rare for a developer to design a pleasing product. This piece can help start this trend. FAQs Are software developers creative? Contrary to popular belief, software developers are creative beasts. Writing good code requires logic as you need to get things done properly, but you also need the creativity to make a good solution. Software developers combine these two skills with excellent drive and efficiency to create software that solves issues and improves the lives of people. Can you learn to build beautiful software? Yes, you can. You practice your coding, learn from your mistakes, and improve your application - this is the same for design. It takes time to develop these skills and to perfect them. Be patient with yourself and work on your skills. It helps to note your lessons and improve upon your mistakes. Doing this will help you build beautiful and elegant software. Is software development an artistic field? Yes, it is. It incorporates the style of a savant with the imagination of a visionary to create software that works as expected. It's like interacting with a wine connoisseur. They take in every part of the process, analyze every detail, and put it together to create the best software for people to use. They put effort into the user interface, the user experience, and functionality. The outcome is elegant software that works well and gives the users what they want. Is building software a hard thing to do? Yes, it is. It takes a lot of time and effort to build elegant software. Software developers hone their skills and practice their coding to create elegant software. They learn from their mistakes and implement their skills to create better software to help people in society. They learn to use different coding tools and methods to create elegant software. They give everything to make the world a better place one code at a time. Are software engineers creative? Software engineers are creative. They work well and remain on topic. They have valuable insight they use to enhance their ideas to improve code and applications. They use their creativity to implement visual and structural changes to the programs. They make software that benefits the users and helps the community at large. Is creativity essential to software development? Yes, it is. The software developers are like other professionals. They take in feedback, analyze it, and creatively formulate solutions. Their decision-making and dedication make them excellent workers with cool insights. They generally follow a routine but have complex processes to solve team and community problems. They are creative and effective in their work. Are there services that need software developers? Yes, there are. Software developers are needed in web development, app development, and specialized coding. They are needed in marketing, programming, and various projects. A software developer's skills are diverse and needed in almost every industry. For these and more thoughts, guides and insights visit my blog at martinbaun.com martinbaun.com

Software Developers Can Build Beautiful Software: Here's How

A few days ago, I underwent an MRI scan. They slid me into a large tube, and for 15 minutes, the machine around me buzzed, hummed, and clicked. At the end of the examination, I received a CD containing the data. What does a good developer do in such a situation? Of course, as soon as they get home, they start examining the data and thinking about how they might extract it using . Python The CD contained a bunch of DLLs, an EXE, and a few additional files for a Windows viewer, which are obviously useless on Linux. The crux was in a folder named DICOM. It held a series of extension-less files across eight folders. ChatGPT helped me figure out that is a standard format typically used for storing MRI, CT, and X-ray images. Essentially, it's a simple packaging format containing grayscale images along with some metadata. DICOM The allows you to easily export the files in PNG format: following code import os
import pydicom
from PIL import Image
import sys

def save_image(pixel_array, output_path):
    if pixel_array.dtype != 'uint8':
        pixel_array = ((pixel_array - pixel_array.min()) / (pixel_array.max() - pixel_array.min()) * 255).astype('uint8')

    img = Image.fromarray(pixel_array)
    img.save(output_path)
    print(f"Saved image to {output_path}")

def process_dicom_directory(dicomdir_path, save_directory):
    if not os.path.exists(save_directory):
        os.makedirs(save_directory)

    dicomdir = pydicom.dcmread(dicomdir_path)

    for patient_record in dicomdir.patient_records:
        if 'PatientName' in patient_record:
            print(f"Patient: {patient_record.PatientName}")

        for study_record in patient_record.children:
            if 'StudyDate' in study_record:
                print(f"Study: {study_record.StudyDate}")

            for series_record in study_record.children:
                for image_record in series_record.children:
                    if 'ReferencedFileID' in image_record:
                        file_id = list(map(str, image_record.ReferencedFileID))
                        file_id_path = os.path.join(*file_id)
                        print(f"Image: {file_id_path}")

                        image_path = os.path.join(os.path.dirname(dicomdir_path), file_id_path)
                        
                        modified_filename = '_'.join(file_id) + '.png'
                        image_save_path = os.path.join(save_directory, modified_filename)

                        try:
                            img_data = pydicom.dcmread(image_path)
                            print("DICOM image loaded successfully.")
                            save_image(img_data.pixel_array, image_save_path)
                        except FileNotFoundError as e:
                            print(f"Failed to read DICOM file at {image_path}: {e}")
                        except Exception as e:
                            print(f"An error occurred: {e}")

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: python dicomsave.py <path_to_DICOMDIR> <path_to_save_images>")
        sys.exit(1)
    
    dicomdir_path = sys.argv[1]
    save_directory = sys.argv[2]
    process_dicom_directory(dicomdir_path, save_directory) The code expects two parameters. The first is the path to the DICOMDIR file, and the second is a directory where the images will be saved in PNG format. To read the DICOM files, we use the library. The structure is loaded using the function, from which metadata (such as the patient's name) and studies containing the images can be extracted. The image data can also be read with . The raw data are accessible through the field, which the function converts to PNG. It's not too complicated. Pydicom pydicom.dcmread dcmread pixelarray save_image The result is a few squares (typically 512x512) grayscale images, which can be easily utilized later on. Why did I think it was important to write this short story about my adventure using the DICOM format? When a programmer hears about processing medical data, they might think it's something serious, something that only universities and research institutes can handle (at least, that's what I thought). As you can see, we're talking about simple grayscale images, which are very easy to process and ideal for things like neural network processing. Consider the possibilities this opens up. For something like a simple tumor detector, all you need is a relatively straightforward convolutional network and a sufficient number of samples. In reality, the task isn't much different from recognizing dogs or cats in images. To illustrate how true this is, let me provide an example. After a brief search on Kaggle, where brain tumors are classified based on MRI data (grayscale images). The dataset categorizes the images into four groups: three types of brain tumors and a fourth category with images of healthy brains. The architecture of the network is as follows: I found a notebook ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ conv2d (Conv2D)                 │ (None, 164, 164, 64)   │         1,664 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d (MaxPooling2D)    │ (None, 54, 54, 64)     │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_1 (Conv2D)               │ (None, 50, 50, 64)     │       102,464 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_1 (MaxPooling2D)  │ (None, 16, 16, 64)     │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_2 (Conv2D)               │ (None, 13, 13, 128)    │       131,200 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_2 (MaxPooling2D)  │ (None, 6, 6, 128)      │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_3 (Conv2D)               │ (None, 3, 3, 128)      │       262,272 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_3 (MaxPooling2D)  │ (None, 1, 1, 128)      │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ flatten (Flatten)               │ (None, 128)            │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense (Dense)                   │ (None, 512)            │        66,048 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense_1 (Dense)                 │ (None, 4)              │         2,052 │
└─────────────────────────────────┴────────────────────────┴───────────────┘ As you can see, the first few layers consist of a convolution and max pooling sandwich, which extracts patterns of tumors, followed by two dense layers that perform the classification. This is exactly the same architecture used in that uses the CIFAR-10 dataset. I remember it well, as it was one of the first neural networks I encountered. The dataset contains 60,000 images categorized into ten classes, including two classes for dogs and cats, as I mentioned earlier. The architecture of the network looks like this: TensorFlow's CNN sample code CIFAR-10 Model: “sequential”
_________________________________________________________________
Layer (type) Output Shape Param # 
=================================================================
conv2d (Conv2D) (None, 30, 30, 32) 896 
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 15, 15, 32) 0 
_________________________________________________________________
conv2d_1 (Conv2D) (None, 13, 13, 64) 18496 
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 6, 6, 64) 0 
_________________________________________________________________
conv2d_2 (Conv2D) (None, 4, 4, 64) 36928 
_________________________________________________________________
flatten (Flatten) (None, 1024) 0 
_________________________________________________________________
dense (Dense) (None, 64) 65600 
_________________________________________________________________
dense_1 (Dense) (None, 10) 650 
=================================================================
Total params: 122,570
Trainable params: 122,570
Non-trainable params: 0
_________________________________________________________________ It's clear that we are dealing with the same architecture, just with slightly different parameters, so recognizing brain tumors in MRI images is indeed not much more difficult than identifying cats or dogs in pictures. Furthermore, the mentioned Kaggle notebook is capable of classifying tumors with 99% effectiveness! I just want to point out how simple it can be to extract and process medical data in certain cases and how problems that seem complex, like detecting brain tumors, can often be quite effectively addressed with simple, traditional solutions. Therefore, I would encourage everyone not to shy away from medical data. As you can see, we are dealing with relatively simple formats, and using relatively simple, well-established technologies (convolutional networks, vision transformers, etc.), a significant impact can be achieved here. If you join an open-source healthcare project in your spare time just as a hobby and can make even a slight improvement to the neural network used, you could potentially save lives!

Can You Open Medical Data (MR, CT, X-Ray) in Python and Find Tumors With AI?! Maybe

আপনি কি পাইথনে মেডিকেল ডেটা (এমআর, সিটি, এক্স-রে) খুলতে পারেন এবং এআই দিয়ে টিউমার খুঁজে পেতে পারেন?! হতে পারে

Können Sie medizinische Daten (MR, CT, Röntgen) in Python öffnen und Tumore mit KI finden?! Vielleicht

¿Se pueden abrir datos médicos (RM, tomografía computarizada, rayos X) en Python y encontrar tumores con IA? Tal vez

Pouvez-vous ouvrir des données médicales (IRM, CT, rayons X) en Python et rechercher des tumeurs avec l'IA ?! Peut être

क्या आप पाइथन में मेडिकल डेटा (एमआर, सीटी, एक्स-रे) खोल सकते हैं और एआई के साथ ट्यूमर ढूंढ सकते हैं?! शायद

Pythonで医療データ（MR、CT、X線）を開き、AIで腫瘍を見つけることができるか？！ おそらく

의료 데이터(MR, CT, X-Ray)를 Python으로 열고 AI로 종양을 찾을 수 있습니까?! 아마도

Você pode abrir dados médicos (ressonância magnética, tomografia computadorizada, raio-X) em Python e encontrar tumores com IA?! Talvez

Можете ли вы открыть медицинские данные (МР, КТ, рентген) на Python и найти опухоли с помощью ИИ?! Может быть

Python'da Tıbbi Verileri (MR, CT, X-Ray) Açabilir ve Yapay Zekayla Tümörleri Bulabilir misiniz?! Belki

Bạn có thể mở dữ liệu y tế (MR, CT, X-Ray) bằng Python và tìm khối u bằng AI không?! Có lẽ

你能用 Python 打开医疗数据（MR、CT、X 射线）并用 AI 查找肿瘤吗？！也许吧

PAYTIENT

paytient.com

-- employees

Since n.d.

COMPANY RANKING

PAYTIENT

EVERGREEN INDEX #7384

Representing this company? Click here to claim and customize this page!

Paytient WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

PAYTIENT

paytient.com

-- employees

Since n.d.

COMPANY RANKING

PAYTIENT

EVERGREEN INDEX #7384

RELATED COMPANIESRANK

STORIES ABOUT PAYTIENT

Representing this company? Click here to claim and customize this page!

Paytient WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!