Advancing health care technologies are crucial for doctors and patients. They could make medical services easier to provide while giving people better results, but only if everyone understands the bigger picture. Artificial intelligence (AI) is a critical tool that may become part of your health care services in the near future. Check out how physicians are using AI in medical imaging and diagnostics to learn why it could revolutionize the industry. What Is Medical Imaging Technology? Medical imaging technology is any tool that creates images of tissues and organs to monitor normal and abnormal cases. The term includes various services that assist health care providers in making diagnoses. While they’ve existed long before automation, artificial intelligence in medical imaging is becoming more widespread through software updates. Different Types of Imaging Techniques You’ll better understand why AI could be an essential scientific tool if you know which imaging techniques people undergo. Learn more about each form of technology to understand AI’s advantages and challenges more easily. X-Rays X-ray machines are penetrative imaging tools that look at targeted areas inside the body before sending the results to imaging technology. The machine sends ionizing radiation into a patient to gather pictures for diagnosis. X-rays are especially useful for bone inquiries because the radiation passes through them and makes them bright white. Magnetic Resonance Imaging (MRI) If you need an MRI, a doctor might inject a contrast agent into your bloodstream to make the images clearer before you sit in the machine. Radiowaves, a magnet and a computer processor look inside the selected part of your body to reveal everything from tissues to joints. Ultrasounds Ultrasound imaging doesn’t use any radiation to see what’s in your body. The machinery bounces soundwaves off of your organs and tissues instead. This isn’t a penetrative imaging technique, even though tools like transvaginal wands do work inside the vaginal canal. Computed Tomography (CT) Scans Doctors needing more complex imaging may order CT scans. They combine an X-ray with a computer to send energy through the body before it bounces back on a plate behind the patient. The machinery scans in a circle, making it more useful for 3D images of internal damage or tumors. How Each Technique Benefits From AI If health care experts have used imaging techniques since before AI existed, why would they benefit from it? There are a few key ways AI in medical imaging and diagnostics could improve each technique for providers and patients. Algorithms Can Process Images Faster When doctors order penetrative imaging, they wait for specialized hospital staff to conduct the process and return the pictures. The physician needs time to sit and analyze the image, which may not happen immediately if they have a busy schedule. Given that the U.S. will have a health care worker shortage of over 100,000 jobs by 2028, the high work demand on doctors is a long-term challenge. You don’t need to worry about not getting medical imaging results back quickly if your local hospital uses machine-learning algorithms to process patient results. AI can review results with image interpretation technology, providing recommendations for doctors when they have time to check the scans. A health care provider will still review your results, but they could get back to you faster with computerized assistance. AI May Catch Small Details Better Artificial intelligence in medical imaging can do much more than summarize scans. The algorithms can also delineate structures in the human body. Advanced programs know how to identify cells, tumors, and blood vessels and catch abnormalities in imaging results. Doctors might accidentally overlook similar developments if they’re too small to see with the human eye. Instead of going back for additional imaging in a few weeks or months, you could get earlier and more precise results with AI-supported medical imaging techniques. Remember — your doctor will still have the final say over your diagnosis. AI provides additional insights, but you’ll always need to talk with your health care provider before moving forward with treatments. Predictive Analytics May Provide Personalized Treatment Suggestions Personalized treatment plans start with diagnostic tools like medical imaging before combining your results with your health history. AI may assist with that process in more hospitals over time. Advanced algorithms can predict disease progression and future complications while checking your scan results. Afterward, your doctor will review its recommended treatment options and use that data to start conversations with you. Together, you’ll decide the next best steps. AI won’t determine how you get medical care. Machine learning programs are an evergrowing tool that could make those conversations more straightforward by supplying potentially more accurate data. Real-Time Surgery Imaging Could Become More Effective Some surgeries require medical imagery techniques for real-time data. Machine learning is expanding into operating rooms in specialties like cardiothoracic, ophthalmology and general surgery. When health care professionals use it in real time, the algorithms can review images guiding surgeons through a procedure and assist in augmented visualization. Decision support may also be helpful for instant recommendations based on the patient’s collective medical history, like the likelihood of complications. Does AI Medical Imaging Guarantee Increased Efficiency? There’s no guarantee that AI medical imaging will increase the efficiency of real-time surgical decisions, diagnoses or treatment plans. Algorithms are only as good as their programming. Your doctor will always need to consider the data provided by any machine learning program before using their comprehensive medical knowledge and understanding of your needs to give an informed opinion. Potential Challenges Hospitals May Face As more hospitals start using AI programs to read results like medical scans, it’s important to understand the barriers that may prevent implementation. Keep those factors in mind if you’re hoping to see AI-assisted medical services where you live. Data Storage and Protection Everything processed and produced by artificial intelligence in medical imaging consists of sensitive data. Hospitals need robust storage capabilities to utilize AI-assisted medical imaging and keep patient information safe. Experts estimate data breaches affected 85 million health care records in 2024 and may get worse in years to come. Hospital administrative teams may need to partner with information technology experts internally or externally to set up data storage methods with extra protection. The process may delay AI implementation, depending on where each facility’s current cybersecurity measures stand. Accurate Interpretability Medical imaging technology with AI programs is relatively new. Hospital staff will likely need some form of training before they can use it with patients. Human error could cause less accurate interpretability as medical providers get used to reading and considering AI results while making recommendations. Integrating AI With Current Workflow Systems Adding a software system to a new service is much less complicated than integrating it into something people are already doing. Hospitals are serving patients around the clock, so adding AI to their medical imaging processes without compromising patient care or service speed is challenging. Researchers also point out that health care systems often have fragmented data processes due to things like mismatching software programs or outdated technology. Analyzing, collecting and storing imaging data may require other updates before it can happen smoothly. Communicating AI information across departments or between hospitals may create additional struggles for health care providers. Anticipate More AI in Medical Imaging and Diagnostics Health care professionals are interested in artificial intelligence in medical imaging because it could help them work faster, provide personalized results and give more accurate treatment plans. It can also require complex integration planning before patients benefit from it. Staying up to date on those factors will keep you in the know with the ever-changing health care industry. Advancing health care technologies are crucial for doctors and patients. They could make medical services easier to provide while giving people better results, but only if everyone understands the bigger picture. Artificial intelligence (AI) is a critical tool that may become part of your health care services in the near future. Check out how physicians are using AI in medical imaging and diagnostics to learn why it could revolutionize the industry. What Is Medical Imaging Technology? What Is Medical Imaging Technology? Medical imaging technology is any tool that creates images of tissues and organs to monitor normal and abnormal cases. The term includes various services that assist health care providers in making diagnoses. While they’ve existed long before automation, artificial intelligence in medical imaging is becoming more widespread through software updates. creates images of tissues and organs creates images of tissues and organs Different Types of Imaging Techniques Different Types of Imaging Techniques You’ll better understand why AI could be an essential scientific tool if you know which imaging techniques people undergo. Learn more about each form of technology to understand AI’s advantages and challenges more easily. X-Rays X-Rays X-ray machines are penetrative imaging tools that look at targeted areas inside the body before sending the results to imaging technology. The machine sends ionizing radiation into a patient to gather pictures for diagnosis. X-rays are especially useful for bone inquiries because the radiation passes through them and makes them bright white. Magnetic Resonance Imaging (MRI) Magnetic Resonance Imaging (MRI) If you need an MRI, a doctor might inject a contrast agent into your bloodstream to make the images clearer before you sit in the machine. Radiowaves, a magnet and a computer processor look inside the selected part of your body to reveal everything from tissues to joints. to make the images clearer to make the images clearer Ultrasounds Ultrasounds Ultrasound imaging doesn’t use any radiation to see what’s in your body. The machinery bounces soundwaves off of your organs and tissues instead. This isn’t a penetrative imaging technique, even though tools like transvaginal wands do work inside the vaginal canal. doesn’t use any radiation doesn’t use any radiation Computed Tomography (CT) Scans Computed Tomography (CT) Scans Doctors needing more complex imaging may order CT scans. They combine an X-ray with a computer to send energy through the body before it bounces back on a plate behind the patient. The machinery scans in a circle, making it more useful for 3D images of internal damage or tumors. send energy through the body send energy through the body How Each Technique Benefits From AI How Each Technique Benefits From AI If health care experts have used imaging techniques since before AI existed, why would they benefit from it? There are a few key ways AI in medical imaging and diagnostics could improve each technique for providers and patients. Algorithms Can Process Images Faster Algorithms Can Process Images Faster When doctors order penetrative imaging, they wait for specialized hospital staff to conduct the process and return the pictures. The physician needs time to sit and analyze the image, which may not happen immediately if they have a busy schedule. Given that the U.S. will have a health care worker shortage of over 100,000 jobs by 2028 , the high work demand on doctors is a long-term challenge. of over 100,000 jobs by 2028 of over 100,000 jobs by 2028 You don’t need to worry about not getting medical imaging results back quickly if your local hospital uses machine-learning algorithms to process patient results. AI can review results with image interpretation technology , providing recommendations for doctors when they have time to check the scans. A health care provider will still review your results, but they could get back to you faster with computerized assistance. with image interpretation technology with image interpretation technology AI May Catch Small Details Better Artificial intelligence in medical imaging can do much more than summarize scans. The algorithms can also delineate structures in the human body. Advanced programs know how to identify cells , tumors, and blood vessels and catch abnormalities in imaging results. know how to identify cells know how to identify cells Doctors might accidentally overlook similar developments if they’re too small to see with the human eye. Instead of going back for additional imaging in a few weeks or months, you could get earlier and more precise results with AI-supported medical imaging techniques. Remember — your doctor will still have the final say over your diagnosis. AI provides additional insights, but you’ll always need to talk with your health care provider before moving forward with treatments. Predictive Analytics May Provide Personalized Treatment Suggestions Personalized treatment plans start with diagnostic tools like medical imaging before combining your results with your health history. AI may assist with that process in more hospitals over time. Advanced algorithms can predict disease progression and future complications while checking your scan results. Afterward, your doctor will review its recommended treatment options and use that data to start conversations with you. predict disease progression and future complications predict disease progression and future complications Together, you’ll decide the next best steps. AI won’t determine how you get medical care. Machine learning programs are an evergrowing tool that could make those conversations more straightforward by supplying potentially more accurate data. Real-Time Surgery Imaging Could Become More Effective Some surgeries require medical imagery techniques for real-time data. Machine learning is expanding into operating rooms in specialties like cardiothoracic, ophthalmology and general surgery. When health care professionals use it in real time, the algorithms can review images guiding surgeons through a procedure and assist in augmented visualization. Decision support may also be helpful for instant recommendations based on the patient’s collective medical history, like the likelihood of complications. is expanding into operating rooms is expanding into operating rooms Does AI Medical Imaging Guarantee Increased Efficiency? There’s no guarantee that AI medical imaging will increase the efficiency of real-time surgical decisions, diagnoses or treatment plans. Algorithms are only as good as their programming. Your doctor will always need to consider the data provided by any machine learning program before using their comprehensive medical knowledge and understanding of your needs to give an informed opinion. Potential Challenges Hospitals May Face As more hospitals start using AI programs to read results like medical scans, it’s important to understand the barriers that may prevent implementation. Keep those factors in mind if you’re hoping to see AI-assisted medical services where you live. Data Storage and Protection Everything processed and produced by artificial intelligence in medical imaging consists of sensitive data. Hospitals need robust storage capabilities to utilize AI-assisted medical imaging and keep patient information safe. Experts estimate data breaches affected 85 million health care records in 2024 and may get worse in years to come. affected 85 million health care records affected 85 million health care records Hospital administrative teams may need to partner with information technology experts internally or externally to set up data storage methods with extra protection. The process may delay AI implementation, depending on where each facility’s current cybersecurity measures stand. Accurate Interpretability Medical imaging technology with AI programs is relatively new. Hospital staff will likely need some form of training before they can use it with patients. Human error could cause less accurate interpretability as medical providers get used to reading and considering AI results while making recommendations. Integrating AI With Current Workflow Systems Adding a software system to a new service is much less complicated than integrating it into something people are already doing. Hospitals are serving patients around the clock, so adding AI to their medical imaging processes without compromising patient care or service speed is challenging. Researchers also point out that health care systems often have fragmented data processes due to things like mismatching software programs or outdated technology. Analyzing, collecting and storing imaging data may require other updates before it can happen smoothly. Communicating AI information across departments or between hospitals may create additional struggles for health care providers. often have fragmented data processes often have fragmented data processes Anticipate More AI in Medical Imaging and Diagnostics Health care professionals are interested in artificial intelligence in medical imaging because it could help them work faster, provide personalized results and give more accurate treatment plans. It can also require complex integration planning before patients benefit from it. Staying up to date on those factors will keep you in the know with the ever-changing health care industry.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

How Hospitals Use AI to Boost Efficiency in Medical Imaging Technology

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