About
Physician-Scientist in Cardiovascular Medicine
Postdoctoral Associate at Yale School of Medicine, Department of Internal Medicine, Section of Cardiovascular Medicine.
- Title: Postdoctoral Associate
- Degree: MD, PhD
- Email: minh.h.le@yale.edu
- Institution: Yale University
- Department: Internal Medicine
- ORCID: 0000-0002-7728-1539
Minh Le, MD, PhD, is a physician-scientist in cardiovascular medicine, currently serving as a Postdoctoral Associate at Yale School of Medicine in the Department of Internal Medicine, Section of Cardiovascular Medicine. He graduated from the School of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City (YDS), Vietnam, in 2018 and completed his PhD in Medicine at Taipei Medical University, Taiwan, in 2026.
His research focuses on large language models, computer vision, machine learning, and deep learning, with applications in cardiology and multimodal imaging, including ECG, ultrasound, CT, MRI, and DSA. He is particularly interested in developing clinically deployable AI systems that improve diagnosis, risk stratification, and clinical decision support.
He is a Harvard Medical School alumnus, having completed the Global Clinical Scholars Research Training (GCSRT) Program in 2022. Before joining Yale, Minh spearheaded collaborative AI projects with institutions including Harvard Medical School, Johns Hopkins, and Carnegie Mellon University. His work has been published in leading journals and conferences including JAMA, EClinicalMedicine, IEEE JBHI, IEEE-EMBS, ISBI, ICCV, and MICCAI.
Outside of research, Minh enjoys photography, watching movies, and traveling.
Minh's Profile
Research Interests
My research lies at the intersection of artificial intelligence and cardiovascular medicine, with a focus on developing clinically impactful AI systems across multiple imaging modalities. Clinical interests include hypertrophic cardiomyopathy (HCM), structural heart disease (SHD), transthyretin amyloid cardiomyopathy (ATTR), echocardiography, interventional cardiology, and valvular heart disease.
Cardiovascular AI
Developing AI-driven tools for cardiovascular diagnosis, risk stratification, and clinical decision support using multimodal patient data.
Multimodal Imaging
Computer vision and deep learning applied to cardiac imaging modalities including ECG, echocardiography, CT, MRI, and digital subtraction angiography (DSA).
Large Language Models
Applying LLMs and natural language processing to clinical text, electronic health records, and medical knowledge extraction for cardiovascular care.
Deep Learning
Design and optimization of deep neural networks including convolutional neural networks, transformers, and multimodal architectures for medical applications.
Real-Time Imaging
Real-time medical image interpretation and cardiovascular phenotyping to support point-of-care clinical workflows.
Clinical Trials & Epidemiology
Expertise in clinical trial design, epidemiological methods, meta-analysis, and biostatistical computing for evidence-based cardiovascular medicine.
Collaborating Institutions
Education & Training
Education
Doctor of Philosophy (PhD) in Medicine
2022 - 2026
Taipei Medical University, Taiwan
- International Master/PhD Program in Medicine (IGPM), College of Medicine
- Focus: Artificial Intelligence in Clinical Medicine
- Research Center for Artificial Intelligence in Medicine
Postgraduate Diploma in Epidemiology & Clinical Research
2021 - 2022
Harvard Medical School, Harvard University
- Global Clinical Scholars Research Training (GCSRT) Program
- Training in clinical trials, epidemiology, biostatistics, and grant writing
Doctor of Medicine (MD)
2012 - 2018
University of Medicine and Pharmacy at Ho Chi Minh City (YDS), Vietnam
- General Practitioner program
Professional Experience
Postdoctoral Associate
2026 - Present
Yale School of Medicine, New Haven, CT
- Department of Internal Medicine, Section of Cardiovascular Medicine
- Research in AI, machine learning, and deep learning for cardiovascular medicine
- Focus on multimodal imaging analysis and clinically deployable AI systems
Additional Training
Systematic Review & Meta-Analysis
2017
Johns Hopkins University, Baltimore, MD
Cancer Research & Regenerative Medicine
2017
MD Anderson Cancer Center, University of Texas, Houston
- Training course conducted by the Editor-in-Chief of Cancer Hallmarks
Technical Skills
Computational
- Machine Learning & Deep Learning: PyTorch, TensorFlow, CNNs, Transformers
- Large Language Models, NLP, Computer Vision
- Statistical Analysis: R, STATA, SPSS, Python
- Bioinformatics & Genomics
Clinical & Research
- Clinical Trial Design & Epidemiology
- Meta-analysis & Network Meta-analysis
- Survival Analysis, Propensity Score Matching
- Grant & Proposal Writing
Selected Publications
Published in leading medical journals and top-tier computer science conferences at the intersection of AI and healthcare.
Publication Venues
Research work published in:
For a complete list of publications, please visit my ORCID profile.
Peer Reviewer
Contact
Location
Section of Cardiovascular Medicine
100 Church Street South
New Haven, CT 06519
United States
Minh's Profile