Nigam H Shah

Stanford University

United States

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Articles (24)

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Collaborators (11)

Jennifer Wilson

Assistant Professor

University of California, Los Angeles

UNITED STATES

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Juan Banda

Assistant Professor

University of Georgia

UNITED STATES

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Curtis Langlotz

Professor of Radiology, Medicine, and Biomedical Data Science

Stanford University

UNITED STATES

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Natalie Deuitch

National Human Genome Research Institute

UNITED STATES

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Thomas Valley

University of Michigan

UNITED STATES

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Ben Viggiano

Stanford University

UNITED STATES

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Catherine Aftandilian

Stanford University School of Medicine

UNITED STATES

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Julian Savulescu

National University of Singapore (NUS)

SINGAPORE

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Wei Lu

Singapore University of Technology and Design

SINGAPORE

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Keith Morse

Clinical Assistant Professor

Stanford University School of Medicine

UNITED STATES

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Benjamin Smith

Stanford University School of Medicine

UNITED STATES

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Nigam H Shah

Research Interests

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Articles (24)

Reformulating patient stratification for targeting interventions by accounting for severity of downstream outcomes resulting from disease onset: a case study in sepsis

The Coming AI Revolution in Clinical Trials

Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects

From Better Models to Better Care

Zero-Shot Clinical Trial Patient Matching with LLMs

Medical Ethics of Large Language Models in Medicine

Evaluating the clinical benefits of LLMs

A multi-center study on the adaptability of a shared foundation model for electronic health records

Ethical and regulatory challenges of large language models in medicine

Ensuring useful adoption of generative artificial intelligence in healthcare

Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study

A framework to identify ethical concerns with ML-guided care workflows: a case study of mortality prediction to guide advance care planning.

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks

Characterizing subgroup performance of probabilistic phenotype algorithms within older adults: a case study for dementia, mild cognitive impairment, and Alzheimer’s and Parkinson’s diseases

The Stanford Medicine data science ecosystem for clinical and translational research

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record

The shaky foundations of large language models and foundation models for electronic health records

Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease

Assessing the net benefit of machine learning models in the presence of resource constraints

APLUS: A Python library for usefulness simulations of machine learning models in healthcare

Beta-2 adrenergic receptor agonism alters astrocyte phagocytic activity and has potential applications to psychiatric disease

External validation of AI models in health should be replaced with recurring local validation

Developing medical imaging AI for emerging infectious diseases

Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study

Collaborators (11)

Jennifer Wilson

Juan Banda

Curtis Langlotz

Natalie Deuitch

Thomas Valley

Ben Viggiano

Catherine Aftandilian

Julian Savulescu

Wei Lu

Keith Morse

Benjamin Smith

Make your next move.