GEMS 2027 Thematic Cluster: AI-Enabled Personalised Cardiovascular Care in Malaysia

This thematic cluster will develop and translate culturally responsive, trustworthy, AI-enabled clinical decision support and personalised rehabilitation tools for cardiovascular care in Malaysia. . It operationalises the Monash AI Institute cohort’s Malaysian stream, “Cultural Adaptation of AI Models to a Malaysian Context,” through two clinically grounded PhD projects.

Impact: Cardiovascular disease is a leading global health challenge, while AI models developed predominantly in high-income Western populations may not transfer safely or equitably to Asian settings. By building and validating models in Malaysian cohorts, the cluster will support SDG 3 (Good Health and Well-being) and SDG 10 (Reduced Inequalities), strengthen Monash Malaysia-IJN collaboration, and create pathways to clinically useful decision-support and personalised rehabilitation strategies.

Note: The projects listed below represent two indicative topics within this thematic cluster. If you wish to propose an alternative research topic aligned with this cluster, please consult the designated main supervisor to secure their agreement prior to submitting your application.

Project 1 (Jeffrey Cheah School of Medicine and Health Sciences)

Explainable AI for Early-Onset Heart Failure Risk Stratification

This project will develop and validate clinically interpretable risk-prediction models using de-identified longitudinal electronic medical record data from adults with early-onset heart failure or cardiomyopathy receiving care at Institut Jantung Negara. The models will assess how demographic and routinely collected clinical indicators—including laboratory, medication, ECG, and cardiac imaging variables—contribute to the risk of disease progression, hospital readmission, major adverse cardiovascular events, and mortality, thereby supporting earlier and more targeted clinical intervention. Machine-learning approaches will be benchmarked against standard regression-based models, including logistic regression and Cox proportional hazards models, and evaluated for discrimination, calibration, clinical utility and transportability. Model interpretability will be assessed using transparent feature-attribution and related explanation methods, enabling clinicians to understand how key variables contribute to individual and subgroup predictions.. Particular attention will be given to interpretability, handling missing data, and fairness across sex, age, and Malaysian ethnic groups. Working with clinicians, the candidate will identify actionable predictors and co-design a prototype risk-stratification framework suitable for future evaluation within IJN workflows.

For enquiries, please contact Dr Syafiq Asnawi Zainal Abidin

For more information about this project, please visit our GEMS website.

How to Apply

When you apply for admission into your preferred degree program you will be able to select your scholarship type. No separate application is required.

By clicking on a course, you will be directed to further information, including details on ‘How to Apply’.

However, before applying for a GEMS, it is recommended that you first contact the main supervisor for this GEMS research topic. Please provide details of your academic background and achievements to the supervisor so that they can assess your suitability for the GEMS research topic you are interested in.

Main Supervisor (Malaysia): Dr Syafiq Asnawi Zainal Abidin

Associate Supervisors (Malaysia): Dr Nur Alia Johari , Brig. Gen. Prof. Datuk. Dr Mohd Arshil Moideen (Rtd)

Associate Supervisors (Australia): Professor Emmanuel Stamatakis, Associate Professor Matthew Ahmadi, Dr Nicholas Koemel, Dr Lizhen Qu

Associate Supervisor (External): Dato Sri Dr Azmee Mohd Ghazi (Senior Consultant Cardiologist, IJN, Malaysia)

Project 2 (Jeffrey Cheah School of Medicine and Health Sciences)

Culturally Adaptive AI for Cardiac Rehabilitation After CABG

This project will develop culturally responsive prediction models for cardiac rehabilitation programme (CRP) adherence and longer-term outcomes among adults undergoing coronary artery bypass grafting (CABG) at Institut Jantung Negara. Using an ambispective cohort (target n=1950), the candidate will combine electronic medical record data with surgical and laboratory variables, CRP attendance, functional capacity, and validated Malaysian measures of medication adherence, health literacy, psychological distress, quality of life, and social support. The primary outcome will be CRP adherence, defined as attendance at least 70% of the standard eight-session programme; secondary outcomes will include risk-factor control, readmission, major adverse cardiovascular events and mortality. Multivariable regression modelling (logistic regression, Cox proportional hazards, and Fine-Gray competing-risks models) will form the primary analytic approach, complemented by machine learning (XGBoost and Random Survival Forest with SHAP-based feature attribution) to identify non-linear modifiable barriers and clinically meaningful risk profiles. The work will support targeted, family-inclusive and potentially hybrid or home-based rehabilitation pathways for Malaysia’s multi-ethnic population.

For enquiries, please contact Dr Hamimatunnisa Johar.

For more information about this project, please visit our GEMS website.

How to Apply

When you apply for admission into your preferred degree program you will be able to select your scholarship type. No separate application is required.

By clicking on a course, you will be directed to further information, including details on ‘How to Apply’.

Main Supervisor (Malaysia): Dr Hamimatunnisa Johar

Associate Supervisors (Malaysia): Dr Nur Alia Johari, Dr Muhamad Noor Alfarizal, Dr Syafiq Asnawi, Dr Mogana Darshini Ganggayah

Associate Supervisor (Australia): Professor Emmanuel Stamatakis. Dr Nicholas Koemel, Assoc Prof. Dr Matthew Ahmadi