June 7-11
Yada
Pruksachatkun
Machine Learning Researcher
"Machine Learning + Healthcare: Opportunities and challenges"
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Session: Machine Learning + Healthcare: Opportunities and challenges
Healthcare has become a hot application topic for machine learning researchers and practitioners in recent years. From breast cancer detection to detecting depression on twitter (public health) to mining for insights in the massive archives of COVID-related literature on the internet, there are a myriad of ways that machine learning has been employed to help aid healthcare workers and scientists. However, because of the complex and critical nature of healthcare, there are many challenges to deploying models in real time, including mitigating risk and providing sufficient explainability. In this talk, I will discuss ways that machine learning researchers have tackled problems in healthcare, as well as the obstacles to successful integration of ML into healthcare.
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