Linda Moy

Professor

New York University

United States

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About

Linda Moy is a Professor at New York University in the United States. Her research focuses on the application of artificial intelligence in radiology, including AI algorithmic biases, generative AI, and educational strategies for integrating AI into radiology practice. She has contributed to various professional guidelines and editorial works, showcasing her expertise in the evolving landscape of radiology and machine learning.

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Collaborators (12)

Beatriu Reig

NYU Langone Health

UNITED STATES

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Candace C. Fleischer

UNITED STATES

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Xiaohong Joe Zhou

Professor

University of Chicago

UNITED STATES

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Jean Jeudy

Professor

University of Maryland School of Medicine

UNITED STATES

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Luciano Prevedello

Ohio State University

UNITED STATES

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Francis Deng

Assistant Professor

Johns Hopkins University

UNITED STATES

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Patricia M. Johnson

NYU Langone Medical Center

UNITED STATES

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Tarique Hussain

UT Southwestern

UNITED STATES

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Eddy Solomon

Weill Cornell Medicine

UNITED STATES

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Eric Kim

Clinical Assistant Professor

NYU School of Medicine

UNITED STATES

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Cindy Lee

Assistant Professor

New York University

UNITED STATES

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Radhika Tibrewala

New York University

UNITED STATES

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Linda Moy

Research Interests

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About

Articles (19)

Best Practices for the Safe Use of Large Language Models and Other Generative AI in Radiology

Texts Are More than Notes, They Are Data: A Glimpse into How Machines Understand Text

FastMRI Breast: A Publicly Available Radial k-Space Dataset of Breast Dynamic Contrast-enhanced MRI

Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM

Farewell from the Editor of Radiology

Editorial Opportunities for Radiology Trainees: RSNA’s Radiology: In Training Program

Pitfalls and Best Practices in Evaluation of AI Algorithmic Biases in Radiology

AI-generated Podcast Summaries of Radiology Articles: Analysis of Content and Quality

Editor’s Note 2024: The Year in Review for Radiology

Editor’s Recognition Awards

The U.S. Radiology Residency Match: Update and Multidecade Trends

Ethical Considerations for MRI Research in Human Subjects in the Era of Precision Medicine

Radiology, Chinese Edition

Climate Change and Sustainability

Detecting Common Sources of AI Bias: Questions to Ask When Procuring an AI Solution

New Screening Performance Metrics for Digital Breast Tomosynthesis in U.S. Community Practice from the Breast Cancer Surveillance Consortium

Preoperative Breast MRI Is Not a Significant Prognostic Factor of Recurrence-Free Survival and Overall Survival in Young Women

Women 75 Years Old or Older: To Screen or Not to Screen?

ChatGPT and Other Large Language Models Are Double-edged Swords

Collaborators (12)

Beatriu Reig

Candace C. Fleischer

Xiaohong Joe Zhou

Jean Jeudy

Luciano Prevedello

Francis Deng

Patricia M. Johnson

Tarique Hussain

Eddy Solomon

Eric Kim

Cindy Lee

Radhika Tibrewala

Make your next move.