Arash A Nargesi on Muck Rack

Arash A Nargesi

As seen in: Nature, AHA/ASA Journals
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Articles

Tracing the Pen: Electronic Health Records Amid the Rise of Generative AI

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By Arash A Nargesi, Jacqueline G. You, Danielle S Bitterman, Marc D. Succi, Rebecca G. Mishuris, Eric Poon, Adam Landman
| Nature Verified
Abstract Large language models (LLMs) are poised to transform physician interactions with electronic health records (EHRs) by assisting clinical documentation, drafting preliminary diagnostic reports, and supporting patient communication.
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Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images

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By Arash A Nargesi, Lovedeep S Dhingra, Akshay Khunte, Bobak J. Mortazavi
| AHA/ASA Journals
REFERENCES 1. Wang TJ, Evans JC, Benjamin EJ, Levy D, LeRoy EC, Vasan RS . Natural history of asymptomatic left ventricular systolic dysfunction in the community.Circulation. 2003; 108:977–982. doi: 10.1161/01.CIR.0000085166.44904.79LinkGoogle Scholar 2. Srivastava PK, DeVore AD, Hellkamp AS, Thomas L, Albert NM, Butler J, Patterson JH, Spertus JA, Williams FB, Duffy CI, .
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Detection of Left Ventricular Systolic Dysfunction from Electrocardiographic Images

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By Arash A Nargesi, Lovedeep S Dhingra, Bobak J. Mortazavi, Antonio Ribeiro
| medRxiv
Abstract Left ventricular (LV) systolic dysfunction is associated with over 8-fold increased risk of heart failure and 2-fold risk of premature death. To allow early detection by clinicians, we developed a layout-independent deep learning model that identifies LV systolic dysfunction directly from images of electrocardiograms (ECGs). Overall, 393,910 ECGs with paired echocardiograms were used for model development.
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