Dr Chao Li is a Senior 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 surrouding 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
Expectation-Maximization Regularized Deep Learning for Weakly Supervised
Tumor Segmentation for Glioblastoma
(2021)
Quantifying Structural Connectivity in Brain Tumor Patients
(2021)
12907,
519
(DOI: 10.1007/978-3-030-87234-2_49)
Bayesian optimization assisted unsupervised learning for efficient
intra-tumor partitioning in MRI and survival prediction for glioblastoma
patients
(2020)
Glioblastoma surgery related emotion recognition deficits are associated with right cerebral hemisphere tract changes
– Brain Commun
(2020)
2,
fcaa169
(DOI: 10.1093/braincomms/fcaa169)
Publisher Correction: A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics.
– Scientific Reports
(2020)
10,
13808
(DOI: 10.1038/s41598-020-70346-x)
A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics.
– Scientific Reports
(2020)
10,
9748
(DOI: 10.1038/s41598-020-66691-6)
Semi-automated construction of patient individualised clinical target volumes for radiotherapy treatment of Glioblastoma utilising diffusion tensor decomposition maps
– Br J Radiol
(2020)
93,
20190441
(DOI: 10.1259/bjr.20190441)
Intra-tumoural perfusion habitats showed prognostic value in glioblastoma patients
– Neuro-oncology
(2019)
21,
iv3
Intratumoral Heterogeneity of Glioblastoma Infiltration Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging.
– Clinical Neurosurgery
(2019)
85,
524
(DOI: 10.1093/neuros/nyy388)
Abstracts from the BNOS 2019 Meeting July 3–5, 2019 London, UK
– Neuro-oncology
(2019)
21,
NP
- <
- 2 of 4