Stephen Pfohl

Orcid: 0000-0003-0551-9664

According to our database1, Stephen Pfohl authored at least 24 papers between 2018 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.
J. Am. Medical Informatics Assoc., November, 2023

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking.
CoRR, 2023

Towards Expert-Level Medical Question Answering with Large Language Models.
CoRR, 2023

Adapting to Latent Subgroup Shifts via Concepts and Proxies.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Considerations in the reliability and fairness audits of predictive models for advance care planning.
Frontiers Digit. Health, 2022

Large Language Models Encode Clinical Knowledge.
CoRR, 2022

Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Improving the Fairness of Chest X-ray Classifiers.
Proceedings of the Conference on Health, Inference, and Learning, 2022

2021
Language models are an effective representation learning technique for electronic health record data.
J. Biomed. Informatics, 2021

An empirical characterization of fair machine learning for clinical risk prediction.
J. Biomed. Informatics, 2021

Learning decision thresholds for risk stratification models from aggregate clinician behavior.
J. Am. Medical Informatics Assoc., 2021

A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021.
CoRR, 2021

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations.
CoRR, 2021

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Appl. Clin. Inform., 2021

Machine Learning for Health (ML4H) 2021.
Proceedings of the Machine Learning for Health, 2021

2020
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data.
CoRR, 2020

Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All.
Proceedings of the Machine Learning for Health Workshop, 2020

2019
Federated and Differentially Private Learning for Electronic Health Records.
CoRR, 2019

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Counterfactual Reasoning for Fair Clinical Risk Prediction.
Proceedings of the Machine Learning for Healthcare Conference, 2019

Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Unraveling the Complexity of Amyotrophic Lateral Sclerosis Survival Prediction.
Frontiers Neuroinformatics, 2018

Predicting Inpatient Discharge Prioritization With Electronic Health Records.
CoRR, 2018

Transfer learning to adapt predictive models for pediatric patients in the EHR.
Proceedings of the AMIA 2018, 2018


  Loading...