Stephen Pfohl

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Machine Learning

Top Venues

Frontiers Digit. Health

Publications

Mercy Nyamewaa Asiedu, Awa Dieng, Iskandar Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine A. Heller
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. CoRR (2024)
Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal, Ahmad Beirami, Alex D'Amour, Dj Dvijotham, Adam Fisch, Katherine A. Heller, Stephen Pfohl, Deepak Ramachandran, Peter Shaw, Jonathan Berant
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. CoRR (2023)
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
Towards Expert-Level Medical Question Answering with Large Language Models. CoRR (2023)
Jonathan Lu, Amelia Sattler, Samantha Wang, Ali Raza Khaki, Alison Callahan, Scott L. Fleming, Rebecca Fong, Benjamin Ehlert, Ron C. Li, Lisa Shieh, Kavitha Ramchandran, Michael Gensheimer, Sarah Chobot, Stephen Pfohl, Siyun Li, Kenny Shum, Nitin Parikh, Priya Desai, Briththa Seevaratnam, Melanie Hanson, Margaret Smith, Yizhe Xu, Arjun Gokhale, Steven Lin, Michael A. Pfeffer, Winifred Teuteberg, Nigam H. Shah
Considerations in the reliability and fairness audits of predictive models for advance care planning. Frontiers Digit. Health 4 (2022)
Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi
Improving the Fairness of Chest X-ray Classifiers. CHIL (2022)
Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam Shah
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare. FAccT (2022)
Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Kumar Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Schärli, Aakanksha Chowdhery, Philip Andrew Mansfield, Blaise Agüera y Arcas, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle K. Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan
Large Language Models Encode Clinical Knowledge. CoRR (2022)
Subhrajit Roy, Stephen Pfohl, Girmaw Abebe Tadesse, Luis Oala, Fabian Falck, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew B. A. McDermott, Emily Alsentzer
Machine Learning for Health (ML4H) 2021. ML4H@NeurIPS (2021)
Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen, Luis Oala, Girmaw Abebe, Subhrajit Roy, Stephen Pfohl, Emily Alsentzer, Matthew B. A. McDermott
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. CoRR (2021)
Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS (2020)
Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. AIES (2019)
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. PSB (2019)
Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah
Counterfactual Reasoning for Fair Clinical Risk Prediction. CoRR (2019)
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Y. Ng, Nigam H. Shah
Predicting Inpatient Discharge Prioritization With Electronic Health Records. CoRR (2018)
Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. CoRR (2018)
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. CoRR (2018)