P r e d i c ti n g i n te r ve n ti on on s e t i n th e I CU wi th s wi tc h i n g s tate s p ac e mod e l s . Office: Department of Computer Science and Medicine University of Toronto Office: Pratt 286A 6 King’s College Rd. Previously, she was a Visiting Researcher with Alphabet’s Verily and a post-doc with Dr. Peter Szolovits at IT (CV). Toronto, ON M5S 3G4, Canada Email: marzyeh (at) cs (dot) toronto (dot) eduRead more → She currently serves as a NeurIPS 2019 Workshop Co-Chair, and Board Member of the Machine Learning for Health Unconference. Professor Ghassemi completed her PhD at MIT where her research focused on machine learning in health care. Gha s s e m i , M.* , W u, M.*, Hughe s , M.C . AI for Healthcare Improving health requires targeting and evidence. Counterfactually guided policy transferin clinical settings. Incremental few-shot learning for low- and multi-label medical image pathology classification. 10.Taylor Killian, Marzyeh Ghassemi, and Shalmali Joshi. (2015) Ne ural Informa t i on Proc e ssi ng Syst e m s (NIPS 2015) Workshop on Machine Learning in He a l t hc a re . Marzyeh has 7 jobs listed on their profile. Previously, she was a Visiting Researcher with Alphabet's Verily and a post-doc with Dr. Peter Szolovits at MIT (CV). Ghassemi, M. Wu, M., Feng, M . Professor Ghassemi completed her PhD at MIT where her research focused on machine learning in health care. Marzyeh Ghassemi - Assistant Professor, Faculties of Computer Science In Medical Imaging Meets NeurIPS Workshop, Vancouver, BC, Canada, 2020. Dr. Marzyeh Ghassemi. W2 Laleh Seyyed-Kalantari, Karsten Roth, MengyeRen, Parsa Torabian, Joseph P. Cohen, Marzyeh Ghassemi. - ieee8023/covid-chestxray-dataset Marzyeh targets “Healthy ML”, focusing on creating applying machine learning to understand and improve health. Dr. Marzyeh Ghassemi is an Assistant Professor at the University of Toronto in Computer Science and Medicine, and a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. View Marzyeh Ghassemi’s profile on LinkedIn, the world’s largest professional community. Marzyeh targets “Healthy ML”, focusing on applying machine learning to understand and improve health. In Inductive Biases, Invariances and Generalization in RL (BIG) at ICML, 2020 [arXiv] 11.Arnold Yeung, Shalmali Joshi, Joseph Williams, and Frank Rudzicz. Sequential explanations with mental model-based policies. Marzyeh tackles part of this puzzle with machine learning. *, S z ol ovi t s , P ., a nd Dos hi -Ve l e z , F . This session will cover some of the novel technical opportunities for machine learning in health challenges, and the important progress to be made with careful application to domain. ... she was a Visiting Researcher with Alphabet’s Verily and a post-doc with Dr. Peter Szolovits at MIT (CV). We are building an open database of COVID-19 cases with chest X-ray or CT images. Dr. Marzyeh Ghassemi is an Assistant Professor at the University of Toronto in Computer Science and Medicine, and a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. Ghassemi, M ., Syed, Z., and R.E ., Gut t a g, J.V. Discrete switching-state sy ste ms for ICU vasopr e ssor i nte r ve nti on and we ani ng pr e di c ti ons. Marzyeh Ghassemi is an Assistant Professor at the University of Toronto in Computer Science and Medicine, affiliated with the Vector Institute. Previously, she was a Visiting Researcher with Alphabet's Verily and a post-doc with Dr. Peter Szolovits at MIT (CV).