Nigam H Shah at Stanford University - Research Interests, Publications & Academic Profile

Nigam H Shah

Stanford University

United States

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Research Interests

Health Communication

80%

Health Economics

50%

Clinical Application

50%

Machine Learning In Healthcare

50%

Disease Modeling

40%

Healthcare Delivery

30%

Medical Ethics

30%

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Articles19

Medical Ethics of Large Language Models in Medicine

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Year:

2024

Evaluating the clinical benefits of LLMs

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2024

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

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2024

Ethical and regulatory challenges of large language models in medicine

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2024

Ensuring useful adoption of generative artificial intelligence in healthcare

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2024

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

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2024

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

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2023

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

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Year:

2023

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

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2023

The Stanford Medicine data science ecosystem for clinical and translational research

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2023

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

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2023

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

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2023

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

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2023

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

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2023

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

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Year:

2023

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

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Year:

2023

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

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Year:

2023

Developing medical imaging AI for emerging infectious diseases

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Year:

2022

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

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Year:

2022

Collaborators7

Jennifer Wilson

Assistant Professor

University of California, Los Angeles

UNITED STATES

Juan Banda

Assistant Professor

University of Georgia

UNITED STATES

Curtis Langlotz

Professor of Radiology, Medicine, and Biomedical Data Science

Stanford University

UNITED STATES

Natalie Deuitch

National Human Genome Research Institute

UNITED STATES

Catherine Aftandilian

Stanford University School of Medicine

UNITED STATES

Julian Savulescu

National University of Singapore (NUS)

SINGAPORE

Keith Morse

Clinical Assistant Professor

Stanford University School of Medicine

UNITED STATES

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