I am a computer scientist and expert in magnetic resonance imaging (MRI) with a long-standing commitment to develop and validate robust, clinically-effective computer-aided diagnosis systems. My research areas include machine learning, deep learning and medical imaging. I am committed to lending my expertise in neuroimaging and computer science to facilitate major breakthroughs in the medical field by optimizing imaging acquisition and aiding doctors in disease diagnosis, outcome prediction, image segmentation and interpretation as well as treatment decision-making and assessment.
I have been leading our team of artificial intelligence (AI) for computer aided diagnosis (AI-CAD) to develop algorithms to:
The current AI technique is rapidly moving from an experimental phase to an implementation phase in many fields. It is expected that medical AI will surpass human performance in specific applications within the coming years. Physicians and patients will likely benefit from the human-AI interaction. Since I have distinguished myself as a front-runner in medical imaging-based AI, I look forward to leading this endeavor at Cincinnati Children's Hospital Medical Center.
BS: Electrical Engineering, Tsinghua University, Beijing, China, 1998.
MS: Computer Science, University of Missouri, Columbia, MO, 2003.
PhD: Computer Science and Engineering, University of Connecticut, Storrs, CT, 2008.
Post-Doc: Massachusetts General Hospital, Harvard Medical School, Boston, MA, 2010.
Machine learning; deep learning; medical image processing and analysis
Multi-site, multi-vendor development and validation of a deep learning model for liver stiffness prediction using abdominal biparametric MRI. European Radiology. 2025; 35:4362-4373.
RadCLIP: Enhancing Radiologic Image Analysis Through Contrastive Language-Image Pretraining. Journal of Central South University. 2025; PP:1-10.
Maternal Hypertension and Adverse Neurodevelopment in a Cohort of Preterm Infants. JAMA Network Open. 2025; 8:e257788.
Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data. 2025; 38:1016-1027.
Role of Complement in the Development of Hypertensive Nephropathy. 2025; 40:308-312.
Canagliflozin ameliorates ferritinophagy in HFpEF rats. Journal of geriatric cardiology : JGC. 2025; 22:178-189.
Liver fibrosis classification on trichrome histology slides using weakly supervised learning in children and young adults. Journal of Pathology Informatics. 2025; 16:100416.
Canagliflozin attenuates kidney injury, gut-derived toxins, and gut microbiota imbalance in high-salt diet-fed Dahl salt-sensitive rats. Renal Failure. 2024; 46:2300314.
Association between circulatory complement activation and hypertensive renal damage: a case-control study. Renal Failure. 2024; 46:2365396.
Lili He, PhD12/31/2019