With the rapid increase of electronic health records (EHR), machine learning researchers have immense opportunities to adopt artificial intelligence into diverse clinical applications. To properly employ artificial intelligence for medicine, Jinsung Yoon, a Research Scientist at Google, tried to handle the special properties of the EHR and clinical applications and to construct end-to-end machine learning frameworks for clinical decision support.
Jinsung proposed various novel machine learning frameworks that can be applicable to a wide range of clinical applications in practical settings. Those models are broadly utilized including cohorts in the intensive care units, wards, and primary care hospitals. Those works consistently and significantly improved state-of-the-art models for handling missing data, understanding the trained model, and generating private synthetic data that is critical for building end-to-end artificial intelligence models for medicine.
Jinsung’s research interests are not limited to artificial intelligence for medicine. He is actively working on diverse and critical research topics in artificial intelligence, such as anomaly detection, self-and semi-supervised learning, and time-series modeling. Recently, Google Covid-19 forecasting models, in which Jinsung participated as the main model developer, got significant attention in both the United States and Japan. The forecasting models were widely used by the US state governments and healthcare providers during the Covid-19 pandemic. As explained above, his endless and passionate innovations would be deeply beneficial in both industries and academia.