Sheikh M. Shariful Islam, MBBS, MPH, PhD, FESC.

Research Interests

Dr. Islam’s research focuses on developing and deploying AI-powered tools for early detection, risk prediction, and personalized management of chronic diseases, particularly cardiovascular and metabolic conditions. His work integrates multimodal data from wearables, imaging, speech, and electronic health records to create scalable digital health interventions.

Key areas of interest include:

• AI-driven digital biomarkers for subclinical disease detection and predicting health worsening
• Just-in-time adaptive interventions (JITAIs) for health, nutrition and lifestyle management
• Federated learning and large language models (LLMs) for personalized care
• Population health modeling to inform equitable health policies

Education

• PhD in Medical Research (International Health)
  Ludwig-Maximilians-Universität München, Germany
• Master of Public Health (MPH), Epidemiology
• MBBS (Hons)

Courses

NS-6350 Advanced Research Methods

NS-4352 Nutrition Technology I-Physiology

NS-4353 Nutrition Technology II-Pathology

Selected Publications

Islam SMS, Miranda JJ, Zoungas S, Maddison R. Premature mortality projections to inform clinical practice and public health priorities. The Lancet Regional Health–Western Pacific. 2024.

Islam SMS et.al. The burden and trend of diseases and their risk factors in Australia, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2023.

Islam SMS et al. The burden of diseases and their risk factors in Bangladesh, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Global Health. 2023.

Rahman MS, Karmakar C and Islam SMS. Application of Federated Learning in Cardiology: Key Challenges and Potential Solutions. Mayo Clinic Proceedings: Digital Health. 2024. 5.

Islam SMS et al. Perceptions of healthcare professionals and patients with cardiovascular diseases on mHealth lifestyle apps: A qualitative study. International Journal of Medical Informatics. 2024.

Islam SMS et al. The burden of type 2 diabetes in Australia during the period 1990–2019: Findings from the global burden of disease study. Diabetes Research and Clinical Practice. 2023.

Moreno SV… Islam SMS. The burden of cardiovascular disease attributable to high dietary sodium intake in Australia between 1990 and 2019. Journal of Hypertension.

Moreno SV….Islam SMS. The burden of cardiovascular disease attributable to dietary risk factors in Australia between 1990 and 2019. PloS One. 2024.

George ES.. Islam, SMS. The burden of non‐alcoholic fatty liver disease in Australia: an analysis of Global Burden of Disease study from 1990 to 2019. Internal Medicine Journal. 2024

Moses JC… Islam SMS. Non-invasive blood glucose monitoring technology in diabetes management. Mhealth. 2024.

Haque R.. Islam SMS. NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data. Scientific Reports. 2024.

Xu X, Islam SMS et al. The contribution of raised blood pressure to all-cause and cardiovascular deaths and disability-adjusted life-years (DALYs) in Australia: Analysis of global burden of disease study from 1990 to 2019. PloS One. 2024.

Moses JC, Adibi S, Angelova M and Islam SMS. Time‐domain heart rate variability features for automatic congestive heart failure prediction. ESC Heart Failure. 2023.

Islam SMS and Maddison R. Beyond statistics: health inequities in rural and remote communities of Australia–Authors' reply. The Lancet Public Health. 2023.

Lobo EH…. Islam SMS. Design and development of a smartphone app for hypertension management: An intervention mapping approach. Frontiers in Public Health. 2023.

Nematollahi MA…. Islam SMS. Body composition predicts hypertension using machine learning methods: a cohort study. Scientific Reports. 2023.

Islam SMS et al. Burden of hypertensive heart disease and high systolic blood pressure in Australia from 1990 to 2019: results from the global burden of diseases study. Heart, Lung and Circulation. 2023

Mahmud S….. Islam SMS. Automated grading of prenatal hydronephrosis severity from segmented kidney ultrasounds using deep learning. Expert Systems with Applications. 2024.

Islam SMS et al. Machine Learning Models for the Identification of Cardiovascular Diseases Using UK Biobank Data. arXiv preprint arXiv. 2024.

Charchar F…Islam SMS et al. Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension. Journal of hypertension. 2024.

Sharifrazi D … Islam SMS. Hypertrophic cardiomyopathy diagnosis based on cardiovascular magnetic resonance using deep learning techniques. Human-centric Computing and Information Sciences. 2023.

Dening J.., Islam SMS. A web-based low carbohydrate diet intervention significantly improves glycaemic control in adults with type 2 diabetes: results of the T2Diet Study randomized controlled trial. Nutrition & Diabetes. 2023.

Islam SMS et al. Wearable Cuffless Blood Pressure Monitoring Devices: A Systematic Review and Meta-Analysis. European Heart Journal-Digital Health. 2022.

Fellowships and Leadership Committees

Fellow, European Society of Cardiology and Member, eCardiology

Fellow, International Society of Hypertension and Member, Asia-Pacific Regional Advisory Committee

Fellow, European Heart Failure Association and Member, Cardiac Devices Committee

Chair, Cardiac Society of Australia and New Zealand IT Committee AI in Cardiology

Founding Executive Committee Member, and Chair, Early Career Committee, Australasian Society for Physical Activity (ASPA)

Leader, WHO-ITU Working Group, AI for Health, Cardiology topic Group

Chair, Organizing Committee, International Conference on NCDs, Munich, Germany