AI Is Laying the Foundation for Tomorrow’s MedTech

September 7, 2018 - 3 minutes read

MedTech app developerArtificial intelligence (AI) will make its mark on every industry, sooner or later. Fortunately, we don’t have to wait to see it happen in MedTech development. AI’s promising potential for healthcare was recently lauded by the American Medical Association (AMA). The possibilities are endless and “in a way that outperforms what either can do alone,” says a very hopeful AMA.

There are several organizations working to augment healthcare with AI. These companies are leading the way by setting a new standard.

Cardiac Arrest & Cancer Prevention

A new tool dubbed “Doctor Hazel” uses AI, specifically deep learning, to screen and diagnose skin cancers with an 80% accuracy rate. The bot’s builders, a team called BlueScan, are now using Doctor Hazel’s technology to build a bigger cancer detection engine.

Microsoft’s also jumping in the game: it developed an AI-powered platform for physicians to use at Ochsner Medical Center in New Orleans. It predicts and can prevent patients from coding (going into cardiac or respiratory arrest). When used over the course of three months, the hospital saw a decrease in codes by 44%.

Joseph Kvedar is the Vice President of Connected Health at Partners HealthCare. He recently wrote about what the future of healthcare would look like with AI in the mix. Kvedar says accepting AI and other technologies is not easy for physicians, but these technologies are indispensable in revolutionizing the current healthcare model.

Medical Imaging & Machine Learning

Radiology, a largely analytical and visual medical specialty, is one of the first fields that industry experts think will be shaken up by AI. According to Signify Research, the international market for machine learning in medical imaging is set to exceed $2 billion by 2023.

In Boston, a research team comprised of scientists and physicians from Massachusetts General Hospital, Brigham, and Women’s Hospital Center for Clinical Data Science are using deep neural networks running on integrated systems. AI can read these systems with ease; in fact, it can go through 10 million radiology records in much less time than a human would take.

The collaboration may lead to the deep learning networks being able to deduce information about human tissue with better precision than today’s lab scientists.

Accepting AI

According to JASON, an independent research group, AI has already started transforming healthcare. However, the report conceded, there are “significant challenges” to the technology, including helping physicians accept yet another technology.

The AMA has already decided that it will continue exploring AI applications and its legal implications. The organization will also prioritize encouraging adoption of AI for practicing physicians, medical school students, nurses and assistants, administrators, and, of course, patients.

Would you let AI identify issues in your x-rays? What about performing surgery on you? It’s important we start thinking about these questions now!

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