When thinking of robotics and AI in healthcare, robotic surgery and exoskeletons are what probably comes to mind first. Yet in reality, there’s a multitude of other ways automation and machine learning are changing medical care practices at their core.
New startups and initiatives emerge every month, many with daring goals and a potential to revolutionize their respected fields. Here’s a quick rundown of the major ways robotics and artificial intelligence are disrupting the healthcare industry right now.
1. Diagnostics and treatment plan creation
If provided with quality input data, AI is extremely efficient at classifying and identifying patterns. It’s no surprise then that this technology—predictive analytics, self-learning algorithmic solutions, and image analysis tools in particular—is currently being adopted for diagnostics.
Recent examples include advanced endoscopy, visual diagnostics of melanoma, reducing false-positives and improving recall rates in mammography results, and more. More reliable self-diagnosing, although somewhat controversial, is one of the emerging applications as well.
Considered as experimental programs and unique research projects today, they are fully expected to become standard practices in the future, along with the extensive AI integration in all aspects of professional diagnostics and personal treatment planning.
2. Preoperative planning and robot-assisted surgery
Among other rapidly developing medical spheres, robotic surgery (or robot-aided surgery) is another sign of major upcoming shifts in clinic practices. Largely associated with minimally invasive surgeries in public consciousness, the technology can, however, be employed in a variety of situations to enhance precision, reach, navigation, learning and other capabilities of surgeons and physicians alike.
With key pharmaceutical players heavily investing in medical tech and robotic surgery, it’s one of the most promising bets in the field of medical research (and investments) for the foreseeable future. At the moment, though, the adoption rates are slow due to high costs and still relatively small contribution to patients’ health.
However, further AI, AR, and VR integration, accumulation of positive outcomes, and continued demonopolization are expected to bring the costs down and move the adoption process along in the next 10–15 years.
3. Physical therapy, movement assistance, and rehabilitation
Advanced prosthetics and exoskeletons are the true stars of healthcare robotics. Flashy, impressive, and rapidly evolving, they are the most prominent in their field. Exoskeletons in particular, with their potential for both industrial and medical use, are currently one of the bigger investment magnets, projected to reach 5.8B market value in less than a decade.
Other solutions belonging to this category of AI and robotics for motion assistance, physical therapy, and rehabilitation include, but aren’t limited to:
- Robotic physical therapy tools (walking aid equipment and simulators, balance, hand/arm-motion training, and complex routine guidance robots)
- Augmented reality rehabilitation software working in tandem with specialized training equipment (visually aided, proximity and motor skill training after strokes)
- Gamified solutions for recovery and cognitive rehabilitation (facilitating cognitive recovery, anxiety treatment)
For many of these cases robotic tools provide mechanical aid and exercise direction, while AI assists in controlling the process. Built on deep neural networks, AI can track and access a patient’s progress, adjust an exercise program, and inform therapists accordingly. Combined with traditional physical therapy, AI and robotics-assisted programs founded on the latest neurological findings are often able to enhance the results and accelerate patients’ recovery.
4. Virtual nursing and medical assistance
Nursing staff is the backbone of healthcare services, accounting for 3 million jobs in the US alone. Since one of the most promising real-life applications of medical AI is virtual nursing and assistance, it can be easy to perceive automation as a threat to hospital staff jobs, both now and in the future.
In reality, though, this idea couldn’t be further from the truth. Often, when AI is introduced into a profession, the real purpose is not to displace employees but rather to aid, guide and add convenience for everyone involved.
For example, the wide adoption of virtual and remote patient assistance programs can at least partially solve the problem of nursing shortage for understaffed hospitals. Another benefit is professionally assisted home-based recovery and monitoring becoming an option for those unable to otherwise afford or receive medical care. It can also be a solution to hospital bed shortages, or even become a basis for a completely ‘beds-free’ virtual clinical experience.
5. Care and companionship for the elderly
An ideal robot companion is yet to be assembled (and, frankly, conceived), but engineers around the globe are definitely trying. As of mid-2019, fresh startups and new prototypes for home use keep popping up. There are social, companion and therapeutic (“animal”) robots in various stages of production, ideally aimed to perform a multitude of tasks like guidance, alert and notification sending, recognizing and reacting to specific emotions, identifying people, and so on.
Smart voice assistants are the most prominent of them. Little more than smart speakers with some ability to move about and snap a photo or make a recording, they are mobile and unintrusive, and are supposed to help to communicate and battle loneliness and isolation. ElliQ (Intuition Robotics) is among such examples.
Applied in elderly care and household assistance, they can sport motion and falling sensors, access calendars and appointments, learn or be programmed to recognize and respond to unusual situations, like Buddy by Blue Frog Robotics.
The ability to mimic natural speech and support flowing conversation remains the biggest challenge and future goal for such robots, in addition to immersive smart home integration and the increase in the variety of reactions, tasks and voice commands supported.
6. Administrative and management tasks
Running a medical or a research facility is in many ways similar to running a business. It requires managing various tasks and departments, dealing with logistics, legal and administrative paperwork, medical history databases, coordination of collaborative actions, and so on. In the US especially, where less than 20% of hospitals rely on federal or state budget for financing, the questions of funding and making profit add to regular tasks and activities. Combined, all these factors make efficient business intelligence and management software a necessity for any medical facility.
In line with contemporary business trends, these management systems have started to adopt AI alongside automated systems for repetitive tasks, medical record management, staff coordination, data analysis, reporting and more.
7. Privacy, security, and quality assurance of medical databases and software
Quality and compliance assurance (e.g., compliance with IEC 62304 and HIPAA), software testing, security checks, and overall system maintenance should be par for the course in any organization that deals with sensitive information. These measures become even more important when human lives, health, and social security numbers are on the line.
Software can crash, updates of medical history and other databases can fail, and potential breaches and digital system corruptions are often a risk. Human error is ever present, especially when people work double or triple shifts, and have “life-or-death emergency situation decision making” in their job description.
Last year was marked the year of Big Data security breaches, leaks, and hacks. Sadly, medical databases weren’t an exception. To help with security and quality assurance in 2019, cognitive automation solutions, as well as traditional QA can be employed for various checkups. A1QA experts recommend to introduce automated testing to secure medical data and software continuously. Here, AI and machine learning can be integrated into the testing toolkit to ensure better test case analysis, predict possible bottlenecks, and identify weak spots much more quickly.
There is a lot more to healthcare than robots and artificial intelligence systems, but their significance in the industry is undeniable. The technology is still in its fledgling state in many regards, although it picked up steam dramatically in recent years.
While AI and robots won’t completely take over healthcare and displace human professionals anytime soon, it’s nothing short of exciting to follow the developments and watch new tools, enhancements, and augmentations truly shape the future of healthcare.