Chao Li | Faculty of Mathematics

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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-task Learning of Histology and Molecular Markers for Classifying Diffuse Glioma

X Wang, S Price, C Li

(2023)

(link to publication)

CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis

L Jiang, Y Mao, X Chen, X Wang, C Li

(2023)

(link to publication)

DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution

Y Mao, L Jiang, X Chen, C Li

(2023)

(link to publication)

Multi-modal learning for predicting the genotype of glioma

Y Wei, X Chen, L Zhu, L Zhang, C-B Schonlieb, S Price, C Li

– IEEE Trans Med Imaging

(2023)

PP,

1

(doi: 10.1109/TMI.2023.3244038)

Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural Networks

Y Wei, Y Li, X Chen, CB Schönlieb, C Li, SJ Price

– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

(2022)

12962,

140

(doi: 10.1007/978-3-031-08999-2_11)

Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for Glioblastoma

Y Li, C Li, Y Wei, S Price, CB Schönlieb, X Chen

– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

(2022)

12962,

124

(doi: 10.1007/978-3-031-08999-2_10)

Multi-modal learning for predicting the genotype of glioma

Y Wei, X Chen, L Zhu, L Zhang, C-B Schönlieb, SJ Price, C Li

(2022)

(link to publication)

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading

L Zhang, Y Wei, Y Fu, S Price, C-B Schönlieb, C Li

(2022)

(link to publication)

Predicting conversion of mild cognitive impairment to Alzheimer's disease

Y Wei, SJ Price, C-B Schönlieb, C Li

(2022)

(link to publication)

Collaborative Learning of Images and Geometrics for Predicting Isocitrate Dehydrogenase Status of Glioma

Y Wei, C Li, X Chen, CB Schoinlieb, SJ Price

– 2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022)

(2022)

00,

1

(doi: 10.1109/isbi52829.2022.9761407)