Philip Payne

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Janet and Bernard Becker Professor and Director

Washington University in St. Louis

United States

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Philip Payne is the Janet and Bernard Becker Professor and Director at Washington University in St. Louis, USA. His research focuses on artificial intelligence in healthcare, particularly in areas such as phenotype extraction, predictive modeling for neurofibromatosis, and dementia analysis. He has contributed significantly to the understanding of AI’s role in biomedical informatics through various publications exploring AI methodologies and their practical applications in health systems.

Recent Grants

Grant: Close

Research Training in Data Science for Health in Rwanda

Open Date: 2021-09-22

Close Date: 2026-07-31

Grant: Close

CRITICAL: Collaborative Resource for Intensive care Translational science, Informatics, Comprehensive Analytics, and Learning

Open Date: 2021-08-15

Close Date: 2025-07-31

Grant: Close

I/UCRC: Center for Experimental Research in Computer Systems (CERCS) Site

Open Date: 2013-04-01

Close Date: 2014-02-28

Grant: Close

The OSU Clinical and Translational Research Informatics Training Program (CTRIP)

Open Date: 2012-07-01

Close Date: 2018-06-30

Grant: Close

Experimental Therapeutics of Leukemia

Open Date: 2009-08-17

Close Date: 2015-07-31

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2022

Collaborators (13)

Suzanne Schindler

Associate Professor

Washington University in St. Louis

UNITED STATES

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Ahmed Sameh Said

Assistant Professor

Washington University in Saint Louis School of Medicine

UNITED STATES

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Karandeep Singh

Assistant Professor

University of Michigan

UNITED STATES

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Charles P. Friedman

UNITED STATES

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Mackenzie Hofford

Assistant Professor

Washington University Physicians

UNITED STATES

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Randi Foraker

Professor and Chair

University of Missouri System

UNITED STATES

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Seunghwan Kim

Washington University in St. Louis

UNITED STATES

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Nicole Weiskopf

Associate Professor

Oregon Health & Science University

UNITED STATES

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Thomas Kannampallil

Associate Professor & Assoc. Chief Research Information Officer

Washington University in St. Louis

UNITED STATES

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Neel Shah

Assistant Professor

Washington University in St. Louis

UNITED STATES

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Carolyn T. Bramante

University of Minnesota

UNITED STATES

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Genevieve Melton-Meaux

University of Minnesota

UNITED STATES

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Albert Lai

Professor / Chief Research Information Officer

Washington University in St. Louis

UNITED STATES

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Philip Payne

Research Interests

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Recent Grants

Articles (20)

Comparison of rule- and large language model-based phenotype extraction from clinical notes for neurofibromatosis type 1

Toward an artificial intelligence code of conduct for health and healthcare: implications for the biomedical informatics community

Meeting the Artificial Intelligence Needs of U.S. Health Systems

HiMAL: Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting Alzheimer’s disease progression

Leveraging GPT-4 for identifying cancer phenotypes in electronic health records: a performance comparison between GPT-4, GPT-3.5-turbo, Flan-T5, Llama-3-8B, and spaCy’s rule-based and machine learning-based methods

Real world performance of the 21st Century Cures Act population-level application programming interface

Evaluating dimensionality reduction of comorbidities for predictive modeling in individuals with neurofibromatosis type 1

Multi-modal prediction of extracorporeal support—a resource intensive therapy, utilizing a large national database

Examining heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles

mosGraphGen: a novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development

Multi-horizon predictive models for guiding extracorporeal resource allocation in critically ill COVID-19 patients

Electronic health record data quality assessment and tools: a systematic review

Extraction of clinical phenotypes for Alzheimer’s disease dementia from clinical notes using natural language processing

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility

Effect of clinician attention switching on workload and wrong-patient errors

OpenSep: a generalizable open source pipeline for SOFA score calculation and Sepsis-3 classification

Respiratory support status from EHR data for adult population: classification, heuristics, and usage in predictive modeling

Better together: Integrating biomedical informatics and healthcare IT operations to create a learning health system during the COVID‐19 pandemic

Developing real-world evidence from real-world data: Transforming raw data into analytical datasets

Learning from data: A recurring feature on the science and practice of data-driven learning health systems

Collaborators (13)

Suzanne Schindler

Ahmed Sameh Said

Karandeep Singh

Charles P. Friedman

Mackenzie Hofford

Randi Foraker

Seunghwan Kim

Nicole Weiskopf

Thomas Kannampallil

Neel Shah

Carolyn T. Bramante

Genevieve Melton-Meaux

Albert Lai

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