Machine Learning in Healthcare
Will robots inherit the world of healthcare?
Maybe. Probably, but not yet.
And in the meantime, can't we all just get along?
We can more than just get along. While the field of digital health has seen a rise in fully automated "doctor bots" (at least in talk), we have a different view of the emerging discipline of machine learning with regards to healthcare.
We do not believe that physicians will get replaced by robots or that medical specialists and health coaches will be superseded by software. There are many reasons for this beyond just the fact that doctors still know more and only licensed doctors should make clinical decisions affecting patient care. Another reason is purely the accountability that plays a significant role in healing people. Having another person on the other end of the app (a real person with a name and a medical degree) is extremely helpful for both trust and accountability. This, in turn, leads to better outcomes.
Virta sees the partnership with the machine as an augmenter; a force multiplier to medical expertise and the reach of our “house call”
While we have great respect for companies who are exploring straight machine learning to treat patients without the human intervention, we also have great respect for the medical community, physicians, health coaches, nursing staff, counselors, and other experts in the field of human wellness. Which is one of the big reasons that early on, we hired physicians into our growing company. You can read more about our approach to building a “full-stack” tech company in healthcare from our CEO, Sami Inkinen.
Virta data scientists believe in a hybrid model of machine learning algorithms and clinical staff working side by side. Neither change agent alone is sufficient to hit the company goal of reversing type 2 diabetes in 100M people by 2025.
Quite simply, physicians and health coaches provide the medical expertise and accountability to our patients, and machine learning allows us to scale. So while there is often talk of the robots taking our jobs, Virta sees the partnership with the machine as an augmenter; a force multiplier to medical expertise and the reach of our “house call”.
The future of health intervention, assisted by a thoughtful integration of machine assistance, provides an exponential lever to the medical care practitioner. The ways in which machine learning is currently being put into practice is truly inspirational. We recently invited specialists in machine learning to share how they are using the technology to make lives better for patients. See the videos and bios below for more details.
A full-stack data scientist, engineer, and entrepreneur, Abe Gong has used rapid prototyping and data science to solve problems in health, education, and public policy for over a decade. He has led human-centric data teams at three growth-stage startups (Massive Health, Jawbone, and Aspire Healthcare), with consulting and advising engagements at several others. Abe discusses the current and future states of both value-based care and hospital system consolidation within the industry today. More about Abe.
Nasir is a Clinical Informatics Data Scientist here at Virta Health, who has devoted much of his time in enhancing Virta’s models for predicting the risk of leaving the treatment. In his talk, Nasir emphasizes data that is unique to Virta’s intervention and touches on how we communicate the insights to our clinicians & coaches in order to provide more targeted interventions.
Catalin Voss is an artificial intelligence engineer, coming to us from Stanford University, from where he founded Autism Project Glass, expression recognition glasses for autism therapy. Using Google Glass, he and his team have been working to help children diagnosed with autism develop and learn the ability to read emotions to help with social interactions and in creating friendships. More about Catalin.
Jackie is a Data Scientist & Machine Learning Engineer here at Virta. Building models and systems which provide insight into how to improve patient outcomes and increase efficiency for Virta’s Health Coaches is what Jackie cares about most. In her presentation, she discusses why machine learning makes scalable patient care possible at Virta and why it is critical for Virta’s mission.
Yizhen comes to us from Eleven Two Capital, sharing his story of advisers and operations experience from the perspective of both bio and health technology that has been entering the market. In his presentation, Yizhen speaks about the current state of drug development, as well as inefficiencies, and machine learning innovations that he has witnessed in early-stage start-ups seeking funding. More about Yizhhen.