Marzyeh Ghassemi

Massachusetts Institute of Technology

United States

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Articles (19)

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Collaborators (15)

Dakuo Wang

Associate Professor

Northeastern University

UNITED STATES

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Anind K. Dey

Dean and Professor

University of Washington

UNITED STATES

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Monika Krzyzanowska

University Health Network

CANADA

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Richard D Riley

Professor of Biostatistics

University of Birmingham

UNITED KINGDOM

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Paula Dhiman

University of Oxford

UNITED KINGDOM

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Xiaoxuan Liu

University Hospitals Birmingham NHS Foundation Trust

UNITED KINGDOM

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Susanne Gaube

Lecturer / Assistant Professor

University College London

UNITED KINGDOM

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Melissa McCradden

University of Adelaide

AUSTRALIA

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Nathan Taback

Professor, Teaching Stream

University of Toronto

CANADA

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Matthew McDermott

Columbia University

UNITED STATES

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Elaine Nsoesie

UNITED STATES

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Yuzhe Yang

Assistant Professor

University of California, Los Angeles

UNITED STATES

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James Hendler

Rensselaer Polytechnic Institute

UNITED STATES

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Patricia Logullo

University of Oxford

UNITED KINGDOM

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Xuhai Xu

University of Washington

UNITED STATES

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Marzyeh Ghassemi

Research Interests

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Articles (19)

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation

Computational challenges arising in algorithmic fairness and health equity with generative AI

Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

Machine Learning to Allocate Palliative Care Consultations During Cancer Treatment

Mental-LLM

The limits of fair medical imaging AI in real-world generalization

Limiting bias in AI models for improved and equitable cancer care

Settling the Score on Algorithmic Discrimination in Health Care

Using labels to limit AI misuse in health

Insights on the Current State and Future Outlook of Artificial Intelligence in Healthcare From Expert Interviews (Preprint)

Algorithmic Fairness in Chest X-ray Diagnosis: A Case Study

Machine learning and health need better values

In medicine, how do we machine learn anything real?

Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations

Reproducibility in machine learning for health research: Still a ways to go

Do as AI say: susceptibility in deployment of clinical decision-aids

Five principles for the intelligent use of AI in medical imaging

COVID-19 Image Data Collection: Prospective Predictions are the Future

Collaborators (15)

Dakuo Wang

Anind K. Dey

Monika Krzyzanowska

Richard D Riley

Paula Dhiman

Xiaoxuan Liu

Susanne Gaube

Melissa McCradden

Nathan Taback

Matthew McDermott

Elaine Nsoesie

Yuzhe Yang

James Hendler

Patricia Logullo

Xuhai Xu

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