Dr Chao Li


University position

Senior Research Associate

Dr Chao Li is pleased to consider applications from prospective PhD students.

Departments

Department of Applied Mathematics and Theoretical Physics (DAMTP) and Department of Clinical Neurosciences

Home page

https://www.neurosurg.cam.ac.uk/researc...

Research Themes

Clinical and Veterinary Neuroscience

Systems and Computational Neuroscience

Interests

Dr Li is a Senior Research Fellow with expertise in both clinical neuroscience and computation modelling. Dr Li is particularly interested in developing novel machine learning approaches based on imaging and multi-omics data to for personalised management of neurological diseases. His research interest include: image-based AI for precision oncology and mental health; efficacy and safety assessment of AI innovations for clinical translation.

Research Focus

Keywords

neuroimaging

artificial intelligence

computational neuroscience

neuro-oncology

neuroradiology

Clinical conditions

Alzheimer's disease

Cancers

Cognitive impairment

Dementia

Stroke

Traumatic brain injury

Equipment

Computational modelling

Cross-sectional and cohort studies

Immunohistochemistry

Magnetic resonance imaging (MRI)

Neuropsychological testing

Positron Emission Tomography (PET)

Randomised control trials

Collaborators

Cambridge

Zoe Kourtzi

Tomasz Matys

Stephen Price

Carola-Bibiane Schönlieb

Associated News Items


    Publications

    2022

    Wei, Y., Li, C.#, Price, S.J. (2022), “Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma.” IEEE International Symposium on Biomedical Imaging

    2021

    Wei, Y.*, Li, C.*#, Cui, Z., Mayrand, R.C., Zou, J., Wong, A.L., Sinha, R., Matys, T., Schönlieb, C.B. & Price, S.J (2021), “Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients” bioRxiv

    Wu, J.*, Li, C.*, Gensheimer, M., Padda, J., Kato, F., Shirato, H., Wei, Y., Schönlieb, C.B., Price, S.J., Jaffray, D. J., Neal, J.W., Loo, B.W.J., Wakelee, H., Diehn, M. & Li, R (2021), “Radiological tumor classification across imaging modality and histology. ” Nature Machine Intelligence

    2019

    Li, C.*, Wang S., Torheim T., Yan JL., Boonzaier NR., Matys T, Markowetz F. & Price S.J. (2019), “Characterizing tumor invasiveness of glioblastoma using multiparametric magnetic resonance imaging.” Journal of Neurosurgery

    Li, C.*, Yan JL., Torheim T., McLean, MA., Boonzaier, NR., Huang, Y., Yuan J., van Dijken B RJ., Matys, T., Markowetz, F. & Price, S.J. (2019), “Low perfusion compartments in glioblastoma quantified by advanced magnetic resonance imaging and correlated with patient Survival.” Radiotherapy and Oncology