In 2018, Medtronic put the world’s first automatic closed-loop insulin pump and continuous glucose monitoring system on the market. For people living with Type I diabetes, like me, it was game-changing. It’s the closest thing to an artificial pancreas that I’ve ever seen.  My average blood sugar levels came down 20% in 4 months after I started using it. Like I said, game-changing.

Controlling diabetes is a lot of work. With the lows just as dangerous as the highs, diabetics must continuously monitor their blood glucose levels and regularly adjust their insulin levels. For most, these adjustments must be made several times a day and it can be a constant battle and distraction. In addition to monitoring glucose levels, people with diabetes must also monitor carbohydrate intake and exercise, which both impact glucose levels. When you have diabetes, you are never able to forget about it. 

Medtronic’s AI-driven insulin pump performs in many ways just like a fully functioning pancreas. It monitors and assesses glucose levels every five minutes and intuitively adjusts the amount of insulin it delivers twenty-four hours a day. It learns from your glucose trends and insulin delivery and makes adjustments to its delivery program along the way.  In short, it saves me from the burdens of constant monitoring and manual adjustments. 

It’s not just about diabetes. Artificial Intelligence (AI) is revolutionizing all aspects of health care. It fuels the wearable monitors that can alert us about everything from abnormal heart rates and respiration, to excessive UV exposure. The frontier for AI’s contribution to medicine is continually being pushed outward as new research and new patents are revealed. 

Patent Protection 

With new technology and new players continually entering the market, patent protection for AI driven medical technologies is even more critical than ever. Trade secret and copyright law can help protect programming code but patent protection will offer the broader protection that medical technology companies need. 

RELATED: What Lawyers and Clients Need to Know About the Use of Artificial Intelligence


Much of the recent application of AI technologies has focused on its use in diagnostics. There are good reasons for this. It’s a lucrative field for AI companies and a costly one for healthcare practitioners in terms of potential errors and malpractice. 

The history of AI in diagnostics goes back to the 1950s when doctors first started using rudimentary computer systems to assist them in diagnosis. Today’s diagnostic AI, however, looks very different. Chatbots are leveraging complex algorithms, speech recognition, and learning from thousands of cases to help doctors choose the right medications and to help patients assess their symptoms. 

AI is helping to diagnose cancer, determine the size of tumors and assess the prognosis for patients. This saves time, a critical element in cancer treatment. For example, UT Southwestern researchers recently announced the development of software that leverages AI to recognize cancer cells from digital pathology images. With millions of cells in a single tissue sample, pathologists were previously limited to looking only at parts of a sample. The algorithms in this software promise to improve both speed and accuracy.  

This same speed and accuracy are also leveraged in laboratory analyses of fluids and tissues. Rare diseases can now be diagnosed worldwide through the use of facial recognition and big data using AI. 


Ensuring quicker and more accurate diagnoses is just one part of AI’s application in healthcare. It is also impacting patient treatment. 

Drug trials are time-consuming and costly. However, speed is essential in the highly competitive drug industry, just as it is for patients waiting for cures or relief from symptoms. AI can save time by streamlining the planning of clinical trials and through the quick processing of massive amounts of data. But AI isn’t just reducing time and saving money for pharmaceutical companies. AI is also improving clinical trials by providing researchers with analysis of potential participants and remote monitoring of participants’ adherence. With its ability to analyze tens of millions of genetic compounds in a single day, AI is leading breakthroughs in the treatment of major diseases, including Parkinson’s, Multiple Sclerosis and Ebola. 

Within hospitals, AI is driving innovations in triage, ensuring patients get timely treatment. Google’s DeepMind Health and IBM’s Watson are both engaged in improving patient’s experiences and outcomes. In hospital settings, these and other AI platforms help assess patients, track wait times and even determine the quickest ambulance routes. Hospitals are also partnering with companies such as GE to use AI to maximize operational flow and allow staff to see far more patients in much less time. 


Innovations in AI and robotics are also proving to be surgical game-changers. In 1985, surgeons employed a robot to awkwardly insert a biopsy needle into a patient. Thirty-five years later, surgeons conducted the first ever robotic eye surgery. In February of this year, Medtronic announced the first spinal surgery on a U.S. patient was performed using a combination of AI driven robotics and navigation developed by the company and a partner. In fact, last year alone, over 5,000 robots were employed in well over one million surgeries. 

Da Vinci was the first surgical robot to be approved by the FDA.  Its combination of cameras, surgical tools, analytics and robotic arms continues to be used for a variety of operations in hospitals throughout the U.S. Robots are used today in nearly every type of surgery, from orthopedics to heart surgery. 

Because it is often more precise, robotic surgery is also minimally invasive, resulting in less scarring and faster recoveries for patients. This precision also, for example, allows surgeons to target cancerous cells rather than regions of the body directly. 

AI is being used to stabilize physician’s hands and reduce tremors and to create virtual reality surgical theatres in which surgeons can test out procedures before they see the actual patient. It’s also driving microsurgeries and therapies. The Heartlander, for instance, is a miniature robot that enters the body through a tiny incision and can deliver treatment right on the surface of the heart. 

But the real power of robotic surgery lies in outcomes. Robotic surgeries are far less invasive, produce less scarring and studies are demonstrating that they can drastically reduce hospital stays. 

And for both patients and their doctors this new frontier is looking very promising.