2nd MLFPM Summer School: Finale Doshi-Velez скачать в хорошем качестве

2nd MLFPM Summer School: Finale Doshi-Velez

Second Summer School "Machine Learning Frontiers in Precision Medicine", September 21-23, 2020 Finale Doshi-Velez (Harvard University): Big data in Biology, Opportunities and Challenges In many health settings, we have available a large amounts of longitudinal, partial views of a patient (e.g. what has been coded in health records, or recorded from various monitors). How can this information be used to improve patient care? In this talk, I’ll present work that our lab has done in batch reinforcement learning, an area of reinforcement learning that assumes that the agent may access data but not explore actions. I will discuss algorithms for optimization and off-policy evaluation in the context of actual health applications, pitfalls and fundamental limitations, and how we can move forward via algorithms that engage with human experts. This work is in collaboration with Srivatsan Srinivasan, Isaac Lage, Dafna Lifshcitz, Ofra Amir, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Xuefeng Peng, David Wihl, Yi Ding, Omer Gottesman, Liwei Lehman, Matthieu Komorowski, Aldo Faisal, David Sontag, Fredrik Johansson, Leo Celi, Aniruddh Raghu, Yao Liu, Emma Brunskill, and the CS282 2017 Course. The summer school is part of the H2020 Marie Curie Innovative Training Network "Machine Learning Frontiers in Precision Medicine" (https://mlfpm.eu). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 813533.