
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
Inspired by pathogenic mechanisms: A novel gradual multi-modal fusion framework for mild cognitive impairment diagnosis.
– Neural networks : the official journal of the International Neural Network Society
(2025)
187,
107343
(doi: 10.1016/j.neunet.2025.107343)
Joint modeling histology and molecular markers for cancer classification.
– Medical image analysis
(2025)
102,
103505
(doi: 10.1016/j.media.2025.103505)
Joint Modelling Histology and Molecular Markers for Cancer
Classification
(2025)
Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder
– Neuroradiology
(2025)
67,
921
(doi: 10.1007/s00234-025-03544-x)
Effects of electroconvulsive therapy on functional connectome abnormalities in adolescents with depression and suicidal ideation.
– Journal of affective disorders
(2025)
374,
495
(doi: 10.1016/j.jad.2025.01.071)
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation
– SIAM Journal on Mathematics of Data Science
(2025)
7,
55
(doi: 10.1137/24m1633662)
Group-common and individual-specific effects of structure–function coupling in human brain networks with graph neural networks
– Imaging Neuroscience
(2024)
2,
1
(doi: 10.1162/imag_a_00378)
Knowledge-Driven Subspace Fusion and Gradient Coordination for Multi-modal Learning
– Lecture Notes in Computer Science
(2024)
15004,
263
(doi: 10.1007/978-3-031-72083-3_25)
Unified Modeling Enhanced Multimodal Learning for Precision Neuro-Oncology
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2024)
15181,
1
(doi: 10.1007/978-3-031-73360-4_1)
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