Dr Chao Li is a Principal Research Fellow with expertise in both healthcare and AI innovation, with comprehensive experience in developing image-based AI and multi-omics approaches to model neurological diseases. Dr Li is particularly interested in developing cost-effective AI models and translating these models into healthcare management to promote personalised medicine. His research is surrounding the below themes: 1. Image-based AI for precision mental health. 2. Image-based AI for precision surgical and interventional oncology. 3. Multi-omics AI for disease characterisation and precision medicine. 4. Efficacy and safety assessment of AI innovations for clinical translation and enterprise.
Publications
Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction.
– Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
(2024)
116,
102420
Knowledge-driven Subspace Fusion and Gradient Coordination for
Multi-modal Learning
(2024)
Genomics-guided Representation Learning for Pathologic Pan-cancer Tumor
Microenvironment Subtype Prediction
(2024)
Phy-Diff: Physics-guided Hourglass Diffusion Model for Diffusion MRI
Synthesis
(2024)
Domain Game: Disentangle Anatomical Feature for Single Domain
Generalized Segmentation
(2024)
Cross-modal Diffusion Modelling for Super-resolved Spatial
Transcriptomics
(2024)
Global contextual representation via graph-transformer fusion for hepatocellular carcinoma prognosis in whole-slide images.
– Computerized Medical Imaging and Graphics
(2024)
115,
102378
Brain tumour microstructure is associated with post-surgical cognition
– Scientific reports
(2024)
14,
5646
(doi: 10.1038/s41598-024-55130-5)
Multi-Modal Learning for Predicting the Genotype of Glioma
– IEEE Trans Med Imaging
(2023)
42,
3167
(doi: 10.1109/TMI.2023.3244038)
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