Using Online Classified Ads to Identify the Geographic Footprints of Anonymous, Casual Sex-Seeking Individuals. - Jason A. Fries; Alberto M. Segre; Philip Polgreen (SocialCom/PASSAT, 2012)

Mining the Demographics of Craigslist Casual Sex Ads to Inform Public Health Policy. - Jason A. Fries; Philip M. Polgreen; Alberto M. Segre (ICHI, 2014)

Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction. - Jason Alan Fries (SemEval@NAACL-HLT, 2016)

Data programming with DDLite: putting humans in a different part of the loop. - Henry R. Ehrenberg; Jaeho Shin 001; Alexander J. Ratner; Jason A. Fries; Christopher Ré (HILDA@SIGMOD, 2016)

Snorkel: A System for Lightweight Extraction. - Alexander Ratner; Stephen H. Bach; Henry R. Ehrenberg; Jason Alan Fries; Sen Wu 002; Christopher Ré (CIDR, 2017)

ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information. - Madalina Fiterau; Suvrat Bhooshan; Jason A. Fries; Charles Bournhonesque; Jennifer L. Hicks; Eni Halilaj; Christopher Ré; Scott L. Delp (MLHC, 2017)

SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data. - Jason A. Fries; Sen Wu 002; Alexander Ratner; Christopher Ré (CoRR, 2017)

Snorkel: Rapid Training Data Creation with Weak Supervision. - Alexander Ratner; Stephen H. Bach; Henry R. Ehrenberg; Jason Alan Fries; Sen Wu 002; Christopher Ré (Proc. VLDB Endow., 2017)

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. - Natalia Antropova; Andrew L. Beam; Brett K. Beaulieu-Jones; Irene Chen; Corey Chivers; Adrian V. Dalca; Samuel G. Finlayson; Madalina Fiterau; Jason Alan Fries; Marzyeh Ghassemi; Mike Hughes; Bruno Jedynak; et al. (CoRR, 2018)

Multi-Resolution Weak Supervision for Sequential Data. - Paroma Varma; Frederic Sala; Shiori Sagawa; Jason Alan Fries; Daniel Y. Fu; Saelig Khattar; Ashwini Ramamoorthy; Ke Xiao; Kayvon Fatahalian; James Priest; Christopher Ré (NeurIPS, 2019)

The accuracy vs. coverage trade-off in patient-facing diagnosis models. - Anitha Kannan; Jason Alan Fries; Eric Kramer; Jen Jen Chen; Nigam Shah; Xavier Amatriain (CoRR, 2019)

Medical device surveillance with electronic health records. - Alison Callahan; Jason A. Fries; Christopher Ré; James I Huddleston III; Nicholas J. Giori; Scott L. Delp; Nigam H. Shah (npj Digit. Medicine, 2019)

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (CoRR, 2020)

Trove: Ontology-driven weak supervision for medical entity classification. - Jason A. Fries; Ethan Steinberg; Saelig Khattar; Scott L. Fleming; José D. Posada; Alison Callahan; Nigam H. Shah (CoRR, 2020)

Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. - Sehj Kashyap; Saurabh Gombar; Steve Yadlowsky; Alison Callahan; Jason A. Fries; Benjamin A. Pinsky; Nigam H. Shah (J. Am. Medical Informatics Assoc., 2020)

Estimating the efficacy of symptom-based screening for COVID-19. - Alison Callahan; Ethan Steinberg; Jason A. Fries; Saurabh Gombar; Birju S. Patel; Conor K. Corbin; Nigam H. Shah (npj Digit. Medicine, 2020)

Assessing the accuracy of automatic speech recognition for psychotherapy. - Adam S. Miner; Albert Haque; Jason A. Fries; Scott L. Fleming; Denise E. Wilfley; G. Terence Wilson; Arnold Milstein; Dan Jurafsky; Bruce A. Arnow; W. Stewart Agras; Li Fei-Fei 001; Nigam H. Shah (npj Digit. Medicine, 2020)

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine. - Lin Lawrence Guo; Stephen R. Pfohl; Jason Alan Fries; José D. Posada; Scott L. Fleming; Catherine Aftandilian; Nigam Shah; Lillian Sung (Appl. Clin. Inform., 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Teven Le Scao; Arun Raja; Manan Dey; M. Saiful Bari; et al. (CoRR, 2021)

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR. - Yuyin Zhou; Shih-Cheng Huang; Jason Alan Fries; Alaa Youssef; Timothy J. Amrhein; Marcello Chang; Imon Banerjee; Daniel L. Rubin; Lei Xing 001; Nigam Shah; Matthew P. Lungren (CoRR, 2021)

Language models are an effective representation learning technique for electronic health record data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (J. Biomed. Informatics, 2021)

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. - Stephen H. Bach; Victor Sanh; Zheng Xin Yong; Albert Webson; Colin Raffel; Nihal V. Nayak; Abheesht Sharma; Taewoon Kim 002; M. Saiful Bari; Thibault Févry; Zaid Alyafeai; Manan Dey; et al. (ACL (demo), 2022)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Arun Raja; Manan Dey; M Saiful Bari; Canwen Xu; et al. (ICLR, 2022)

BigBio: A Framework for Data-Centric Biomedical Natural Language Processing. - Jason A. Fries; Leon Weber; Natasha Seelam; Gabriel Altay; Debajyoti Datta; Samuele Garda; Sunny Kang; Rosaline Su; Wojciech Kusa; Samuel Cahyawijaya; Fabio Barth; Simon Ott; et al. (NeurIPS, 2022)

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. - Stephen H. Bach; Victor Sanh; Zheng Xin Yong; Albert Webson; Colin Raffel; Nihal V. Nayak; Abheesht Sharma; Taewoon Kim 002; M. Saiful Bari; Thibault Févry; Zaid Alyafeai; Manan Dey; et al. (CoRR, 2022)

Language Models in the Loop: Incorporating Prompting into Weak Supervision. - Ryan Smith; Jason A. Fries; Braden Hancock; Stephen H. Bach (CoRR, 2022)

BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing. - Jason Alan Fries; Leon Weber; Natasha Seelam; Gabriel Altay; Debajyoti Datta; Samuele Garda; Myungsun Kang; Ruisi Su; Wojciech Kusa; Samuel Cahyawijaya; Fabio Barth; Simon Ott; et al. (CoRR, 2022)

Efficient Diagnosis Assignment Using Unstructured Clinical Notes. - Louis Blankemeier; Jason A. Fries; Robert Tinn; Joseph Preston; Nigam Shah; Akshay Chaudhari (ACL (2), 2023)

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Curtis P. Langlotz; Matthew P. Lungren; Serena Yeung; Nigam Shah; Jason Alan Fries (NeurIPS, 2023)

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models. - Michael Wornow; Rahul Thapa; Ethan Steinberg; Jason A. Fries; Nigam Shah (NeurIPS, 2023)

Self-Supervised Time-to-Event Modeling with Structured Medical Records. - Ethan Steinberg; Yizhe Xu; Jason A. Fries; Nigam Shah (CoRR, 2023)

The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs. - Michael Wornow; Yizhe Xu; Rahul Thapa; Birju S. Patel; Ethan Steinberg; Scott L. Fleming; Michael A. Pfeffer; Jason A. Fries; Nigam H. Shah (CoRR, 2023)

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Matthew P. Lungren; Curtis P. Langlotz; Serena Yeung; Nigam H. Shah; Jason A. Fries (CoRR, 2023)

The shaky foundations of large language models and foundation models for electronic health records. - Michael Wornow; Yizhe Xu; Rahul Thapa; Birju S. Patel; Ethan Steinberg; Scott L. Fleming; Michael A. Pfeffer; Jason Alan Fries; Nigam H. Shah (npj Digit. Medicine, 2023)

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks. - Joshua Lemmon; Lin Lawrence Guo; Ethan Steinberg; Keith E. Morse; Scott Lanyon Fleming; Catherine Aftandilian; Stephen R. Pfohl; José D. Posada; Nigam Shah; Jason Alan Fries; Lillian Sung (J. Am. Medical Informatics Assoc., 2023)

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. - Scott L. Fleming; Alejandro Lozano; William J. Haberkorn; Jenelle A. Jindal; Eduardo Pontes Reis; Rahul Thapa; Louis Blankemeier; Julian Z. Genkins; Ethan Steinberg; Ashwin Nayak 002; Birju S. Patel; Chia-Chun Chiang; et al. (AAAI, 2024)

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records. - Ethan Steinberg; Jason Alan Fries; Yizhe Xu; Nigam Shah (ICLR, 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

Merlin: A Vision Language Foundation Model for 3D Computed Tomography. - Louis Blankemeier; Joseph Paul Cohen; Ashwin Kumar; Dave Van Veen; Syed Jamal Safdar Gardezi; Magdalini Paschali; Zhihong Chen; Jean-Benoit Delbrouck; Eduardo Pontes Reis; Cesar Truyts; Christian Bluethgen; Malte Engmann Kjeldskov Jensen; et al. (CoRR, 2024)

meds_reader: A fast and efficient EHR processing library. - Ethan Steinberg; Michael Wornow; Suhana Bedi; Jason Alan Fries; Matthew B. A. McDermott; Nigam H. Shah (CoRR, 2024)

Assessing the Limitations of Large Language Models in Clinical Fact Decomposition. - Monica Munnangi; Akshay Swaminathan; Jason Alan Fries; Jenelle A. Jindal; Sanjana Narayanan; Iván López; Lucia Tu; Philip Chung 005; Jesutofunmi A. Omiye; Mehr Kashyap; Nigam Shah (CoRR, 2024)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam H. Shah (CoRR, 2024)

A multi-center study on the adaptability of a shared foundation model for electronic health records. - Lin Lawrence Guo; Jason Alan Fries; Ethan Steinberg; Scott Lanyon Fleming; Keith E. Morse; Catherine Aftandilian; José D. Posada; Nigam Shah; Lillian Sung (npj Digit. Medicine, 2024)

Hospitalization prediction from the emergency department using computer vision AI with short patient video clips. - Wui Ip; Maria Xenochristou; Elaine Sui; Elyse Ruan; Ryan Ribeira; Debadutta Dash; Malathi Srinivasan; Maja Artandi; Jesutofunmi A. Omiye; Nicholas Scoulios; Hayden L. Hofmann; Ali Mottaghi; et al. (npj Digit. Medicine, 2024)

Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare. - Lin Lawrence Guo; Keith E. Morse; Catherine Aftandilian; Ethan Steinberg; Jason Alan Fries; José D. Posada; Scott Lanyon Fleming; Joshua Lemmon; Karim Jessa; Nigam Shah; Lillian Sung (BMC Medical Informatics Decis. Mak., 2024)

Time-to-Event Pretraining for 3D Medical Imaging. - Zepeng Frazier Huo; Jason Alan Fries; Alejandro Lozano; Jeya Maria Jose Valanarasu; Ethan Steinberg; Louis Blankemeier; Akshay S. Chaudhari; Curtis P. Langlotz; Nigam Shah (ICLR, 2025)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam Shah (ICLR, 2025)

Red teaming ChatGPT in medicine to yield real-world insights on model behavior. - Crystal T. Chang; Hodan Farah; Haiwen Gui; Shawheen Justin Rezaei; Charbel Bou-Khalil; Ye-Jean Park; Akshay Swaminathan; Jesutofunmi A. Omiye; Akaash Kolluri; Akash Chaurasia; Alejandro Lozano; Alice Heiman; et al. (npj Digit. Medicine, 2025)

Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium. - Amin Adibi; Xu Cao; Zongliang Ji; Jivat Neet Kaur; Winston Chen; Elizabeth Healey; Brighton Nuwagira; Wenqian Ye; Geoffrey Woollard; Maxwell A. Xu; Hejie Cui; Johnny Xi; et al. (CoRR, 2025)

TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records. - Hejie Cui; Alyssa Unell; Bowen Chen; Jason Alan Fries; Emily Alsentzer; Sanmi Koyejo; Nigam Shah (CoRR, 2025)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)