Neal Yuan

Neal Yuan, MD, is an Assistant Professor in the Department of Medicine at the University of California, San Francisco (UCSF), School of Medicine. He completed his medical training at UCSF, followed by a Cardiology Fellowship and Chief Fellowship at Cedars-Sinai Medical Center in 2020. His academic and clinical work bridges cardiology and artificial intelligence, focusing on innovative applications of deep learning in cardiovascular diagnostics and risk prediction.

• Cardiology Fellowship, Chief Fellow – Cedars-Sinai Medical Center (2020)
• Internal Medicine Residency – University of California, San Francisco (2018)
• School of Medicine – University of California, San Francisco (2015)
• Bachelor’s in Molecular Biology, Engineering Biology – Princeton University (2010)

Dr. Yuan’s research centers on leveraging artificial intelligence to transform cardiovascular medicine. His work explores deep learning applications in echocardiography and electrocardiography for detecting conditions such as atrial fibrillation, aortic stenosis, and left ventricular dysfunction. He investigates how AI can improve diagnostic accuracy, reduce variability in ejection fraction calculation, and enable early detection of cardiac and systemic diseases from routine imaging and ECG data. His research also extends to remote patient monitoring, electronic health record optimization, and medication safety.

The most recent articles highlight a strong trend toward multimodal AI systems, particularly vision-language models and video-based biomarkers, applied to echocardiograms and ECGs. These studies emphasize real-world validation, clinical integration, and high-impact applications such as predicting mortality, detecting occult disease, and automating complex diagnostic tasks. The work frequently appears in top-tier journals like Nature, JAMA Cardiology, and The Lancet Digital Health, indicating broad interdisciplinary significance.

While no formal scientific awards are listed, Dr. Yuan’s research has received extensive attention across news outlets, social media, and policy discussions, reflecting its clinical relevance and innovation.

Dr. Yuan has contributed to numerous collaborative research initiatives, particularly with teams at UCLA and UCSF focused on cardiovascular AI. His work often involves high-throughput data analysis, precision phenotyping, and the development of scalable digital tools for clinical use. He has not advised any students listed in the provided material but is deeply embedded in a network of co-investigators advancing digital cardiology.

His lab and team affiliations are centered around cardiovascular AI research, likely within the UCSF Division of Cardiology and affiliated digital health initiatives. His work with Dr. David Ouyang and others suggests involvement in a cutting-edge cardiovascular AI research group focused on translating deep learning models into clinical practice.