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
Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients
(2021)
2021.03.09.434656
(doi: 10.1101/2021.03.09.434656)
Expectation-Maximization Regularized Deep Learning for Weakly Supervised
Tumor Segmentation for Glioblastoma
(2021)
Quantifying Structural Connectivity in Brain Tumor Patients
(2021)
12907 LNCS,
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 communications
(2020)
2,
fcaa169
(doi: 10.1093/braincomms/fcaa169)
A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics (vol 10, 9748, 2020)
– 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
Abstracts from the BNOS 2019 Meeting July 3–5, 2019 London, UK
– Neuro-oncology
(2019)
21,
NP
- <
- 3 of 5
