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Vijay Shah on Muck Rack

Vijay Shah

As seen in: Medium, Nature, MDPI, Medscape, Cell Reports, The Lancet, The Clarion-Ledger, Forbes India, Healio Gastroenterology, The Journal of Biological Chemistry and
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Articles

Clinician engagement shapes the impact of AI-based ECG screening for chronic liver disease in primary care

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By Alberto Calleri, Kan Liu, Blake A. Kassmeyer, Ryan J. Lennon, Puru Rattan, Amir S Seid, Matthew Bernard, Gagandeep Singh, Mark E. Deyo-Svendsen, Graham King Verified, Stephen Stacey, Amy Olofson, Alina Allen, Joseph Ahn, Paul Friedman, Patrick S. Kamath, Zachi I. Attia, Peter A. Noseworthy, Vijay Shah, David R Rushlow, Douglas A Simonetto, Yigit Yazarkan
| Nature Verified
Abstract Artificial intelligence (AI)-based screening tools show promise for early identification of chronic liver disease (CLD), yet their effectiveness in real-world settings may depend on clinician response to AI-generated recommendations. We performed a post hoc analysis of the intervention arm of the pragmatic, cluster-randomized DULCE trial, in which primary care clinicians received electrocardiogram-based machine learning (ECG-ML) alerts indicating elevated risk for CLD.
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Computer Science > Machine Learning

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By Pranshav Gajjar, Vijay Shah, Abiodun Ganiyu
| arxiv.org
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Accelerating AI innovation in healthcare: real-world clinical research applications on the Mayo Clinic Platform - npj Health Systems

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By Yue Stell Yu, Xinyue Hu, Sivaraman Rajaganapathy, Jingna Feng, Ahmed Abdelhameed, Xiaodi Li, Jianfu Li, Xiaoke Liu, Liu Yang, Nilüfer Ertekin-Taner, Richard Larsen, Maneesh Goyal, Nansu Zong, Vijay Shah, John Halamka, Cui Tao, Phil Fiero, Soulmaz Boroumand, Clark C. Otley
| Nature Verified
Abstract Artificial intelligence (AI) holds promise for healthcare, but real-world implementation remains difficult. The Mayo clinic platform (MCP) addresses this by providing scalable, multi-institutional, de-identified data and analytical tools. Through four research projects, we demonstrate MCP’s ability to support efficient cohort identification, AI model development, and real-world evidence generation.
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