Research Projects
Artificial Intelligence and Bioinformatics Approaches for the Diagnosis and Analysis of Rare Paediatric Diseases

Rare paediatric diseases have been difficult to study and predict using traditional AI and machine learning methods due to the small populations affected and difficulty obtaining patient samples, but recent advances in AI and bioinformatics give us a unique opportunity to better understand these complex diseases. Transfer learning AI models provide a way to overcome small population size by harnessing diverse sources of data from other related diseases, from which learnt representations can be transferred over to provide valuable predictions in the disease of interest.

This project aims to design, develop, and implement state-of-the art transfer learning AI models to enable effective diagnosis, prognosis and stratification of disease patients. The student will use transfer learning AI and bioinformatics to identify genomic and phenotypic signatures which increase the risk of paediatric patients developing certain cancers later in life. The project will investigate the utility of explainable AI and representation learning algorithms, which together with bioinformatics techniques, will be used to decipher the molecular and cellular mechanisms of disease and identify potential targets for therapy. Through the integration of multi-omics, medical imaging and electronic health records, the project aims to deliver a precision medicine approach to improve paediatric disease outcomes.

Ideally the student will have some basic experience in computer programming, although training will be provided. The project will provide the student with expertise and training in AI, bioinformatics and precision medicine, as well as the opportunity to collaborate with leading clinical and computational experts.

Dr PD Blakeley, Department of Surgery

HKU Scholars Hub
blakeley@hku.hk

For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

1. your CV,
2. a brief description of your research interest and experience, and
3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to rpgmed@hku.hk.

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.