Arjun K. Manrai on Muck Rack

Arjun K. Manrai

Boston
As seen in: Harvard Medical Labcast, NEJM AI Grand Rounds, Nature, Stanford University, Flipboard, JAMA (The Journal of the American Medical Association), JAMA: Journal of the American Medical Association, The Boston Globe, The New England Journal of Medicine, STAT, International Journal of Epidemiology, medRxiv and
Assistant Professor of Biomedical Informatics, Harvard Medical School @HarvardDBMI | Founding Deputy Editor, @NEJM_AI | Co-host, NEJM AI Grand Rounds
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Articles

Multimodal foundation models exploit text to make medical image predictions

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By Thomas Buckley Verified, James A. Diao, Cam N. Srivastava, Peter G. Brodeur, Pranav Rajpurkar, Adam Rodman, Arjun K. Manrai
| Nature Verified
Abstract Multimodal foundation models have shown compelling but conflicting performance in medical image interpretation. However, the ways in which these models integrate and prioritize different data modalities, including images and text, remain poorly understood. Here we evaluate 8 proprietary and open-source multimodal foundation models using 1090 multimodal medical cases.
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A roadmap for addressing the use of race and ethnicity in clinical algorithms

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By Divya A Shanmugam, Alexandra Chouldechova, James A. Diao, Kadija Ferryman, Arjun K. Manrai, Stephen R Pfohl, Neil R. Powe, Inioluwa Raji, Emma Pierson, Sidhika Balachandar
| Nature Verified
Removing race and ethnicity from clinical algorithms is feasible, but it requires careful evaluation of algorithmic changes and systemic efforts to address underlying disparities. This is a preview of subscription content, access via your institution Access options Subscribe to this journal Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Buy this article Purchase on SpringerLink Instant access to the full article PDF.
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An atlas of exposome–phenome associations in health and disease risk

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By Chirag Patel, John P. A. Ioannidis, Arjun K. Manrai
| Nature Verified
Abstract Nongenetic exposures comprising the ‘exposome’, including diet, lifestyle, infections and pollutants, shape many clinical phenotypes yet the evidence remains fragmented. Here we conducted an exposome-wide association study incorporating 619 exposure indicators and 305 quantitative phenotypes across ten independent waves of the US Centers for Disease Control and Prevention National Health and Nutrition Examination Survey.
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