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个人简介
She works to advance Machine Learning (ML) and Artificial Intelligence (AI) methods with the goal of advancing clinical health and medicine for all.
Artificial Intelligence and Machine Learning, if done right, have a huge potential for transforming health, medicine and improving health equity. reAIM's mission is to refocus methodological developments in Machine Learning and Artificial Intelligence to make ML/AI reliable and safe for health, medicine, and improve health inequities along the way.
Our group develops methods using causal inference, off-policy reinforcement learning, and other advanced deep and machine learning, combined with an in-depth understanding of the clinical problem to develop safe, robust, generalizable learning-based solutions.
Artificial Intelligence and Machine Learning, if done right, have a huge potential for transforming health, medicine and improving health equity. reAIM's mission is to refocus methodological developments in Machine Learning and Artificial Intelligence to make ML/AI reliable and safe for health, medicine, and improve health inequities along the way.
Our group develops methods using causal inference, off-policy reinforcement learning, and other advanced deep and machine learning, combined with an in-depth understanding of the clinical problem to develop safe, robust, generalizable learning-based solutions.
研究兴趣
论文共 38 篇作者统计合作学者相似作者
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AAAI 2024no. 12 (2024): 13004-13012
Stefan Hegselmann,Helen Zhou,Yuyin Zhou, Jennifer Chien, Shivashankar H. Nagaraj, Neha Hulkund, Shreyas Bhave,Michael Oberst, Anil Pai, Caleb Ellington, Wisdom Ikezogwo, Jason Dou,
Zenodo (CERN European Organization for Nuclear Research) (2023)
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Melissa D. McCradden, Oluwadara Odusi,Shalmali Joshi,Ismail Akrout,Kagiso Ndlovu,Ben Glocker, Gabriel Maicas,Xiaoxuan Liu,Mjaye Mazwi, Tee Garnett,Lauren Oakden-Rayner,Myrtede Alfred,
FAccTpp.1505-1519, (2023)
PATTERNSno. 11 (2023): 100864-100864
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