Overview
Background
Dr Cecil Mustafiz is a Junior Doctor at Gold Coast University Hospital with a strong clinical and academic interest in cardiology. He also holds academic appointments as Lecturer at Griffith University, and Associate Lecturer at The University of Queensland.
His research interests include valvular and structural heart disease, acute coronary syndromes and heart failure, with a particular focus on the application of advanced statistical methods and AI-assisted cardiovascular risk stratification and prognostication. He has contributed to peer-reviewed publications in recognised cardiology journals, as well as abstracts and presentations at national and international cardiology conferences.
Dr Mustafiz completed his medical internship at The Prince Charles Hospital and remains actively involved in collaborative research with the Department of Cardiology at The Prince Charles Hospital. Alongside research, he is actively involved in medical education and enjoys teaching and supervising medical students. He also contributes to the academic community as an invited peer reviewer for several medical research journals, including BMC Cardiovascular Disorders, European Journal of Medical Research and Scientific Reports (Nature Portfolio).
Availability
- Dr Cecil Mustafiz is:
- Not available for supervision
Fields of research
Qualifications
- Professional Doctorate of Medicine, Griffith University
- Member, Cardiac Society of Australia and New Zealand, Cardiac Society of Australia and New Zealand
Research interests
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Cardiology
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Valvular Heart Disease
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Acute Coronary Syndromes
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Heart Failure
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Artificial Intelligence
Works
Search Professor Cecil Mustafiz’s works on UQ eSpace
Featured
2025
Journal Article
Machine-learning versus traditional approaches to predict all-cause mortality for acute coronary syndrome: a systematic review and meta-analysis
Gupta, Aashray K., Mustafiz, Cecil, Mutahar, Daud, Zaka, Ammar, Parvez, Razeen, Mridha, Naim, Stretton, Brandon, Kovoor, Joshua G., Bacchi, Stephen, Ramponi, Fabio, Chan, Justin C.Y., Zaman, Sarah, Chow, Clara, Kovoor, Pramesh, Bennetts, Jayme S. and Maddern, Guy J. (2025). Machine-learning versus traditional approaches to predict all-cause mortality for acute coronary syndrome: a systematic review and meta-analysis. Canadian Journal of Cardiology, 41 (8), 1564-1583. doi: 10.1016/j.cjca.2025.01.037
Featured
2025
Journal Article
Spontaneous splenic rupture associated with Q fever and portal hypertension: A case report
Mustafiz, Cecil, Subhaharan, Deloshaan, Chorley, Daniel and Masood, Tariq (2025). Spontaneous splenic rupture associated with Q fever and portal hypertension: A case report. Frontiers in Medicine, 12 1527701, 1-6. doi: 10.3389/fmed.2025.1527701
Featured
2025
Journal Article
Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis
Zaka, Ammar, Mustafiz, Cecil, Mutahar, Daud, Sinhal, Shreyans, Gorcilov, James, Muston, Benjamin, Evans, Shaun, Gupta, Aashray, Stretton, Brandon, Kovoor, Joshua, Mridha, Naim, Sivagangabalan, Gopal, Thiagalingam, Aravinda, Ramponi, Fabio, Chan, Justin, Bennetts, Jayme, Murdoch, Dale J., Zaman, Sarah, Chow, Clara K., Jayasinghe, Rohan, Kovoor, Pramesh and Bacchi, Stephen (2025). Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis. Open Heart, 12 (1) e002779, 1-13. doi: 10.1136/openhrt-2024-002779
Featured
2024
Conference Publication
Machine Learning for Prediction of All-Cause Mortality in Acute Coronary Syndrome
Gupta, Aashray, Zaka, Ammar, Mustafiz, Cecil, Mutahar, Daud, Parvez, Razeen, Stretton, Brandon, Kovoor, Joshua, Mridha, Naim, Ramponi, Fabio, Chan, Justin, Gould, Paul, Sivagangabalan, Gopal, Zaman, Sarah, Thiagalingam, Aravinda, Chow, Clara, Kovoor, Pramesh, Bacchi, Stephen, Bennetts, Jayme and Maddern, Guy (2024). Machine Learning for Prediction of All-Cause Mortality in Acute Coronary Syndrome. American Heart Association's 2024 Scientific Sessions and the American Heart Association's 2024 Resuscitation Science Symposium, Chicago, IL United States, 16–18 November 2024. Philadelphia, PA United States: Lippincott Williams & Wilkins. doi: 10.1161/circ.150.suppl_1.4138355
Featured
2024
Conference Publication
Artificial intelligence for the prediction of all-cause mortality and readmission in heart failure: a meta-analysis of twenty studies
Gupta, Aashray, Zaka, Ammar, Mutahar, Daud, Mustafiz, Cecil, Gorcilov, James, Abtahi, Johayer, Kamalanathan, Harish, Tan, Sheryn, Hains, Lewis, Sharma, Prakriti, Sharma, Srishti, Ragunath, Priyyanca, Kovoor, Joshua, Stretton, Brandon, Mridha, Naim and Bacchi, Stephen (2024). Artificial intelligence for the prediction of all-cause mortality and readmission in heart failure: a meta-analysis of twenty studies. American Heart Association's 2024 Scientific Sessions and the American Heart Association's 2024 Resuscitation Science Symposium, Chicago, IL United States, 16–18 November 2024. Philadelphia, PA United States: Lippincott Williams & Wilkins. doi: 10.1161/circ.150.suppl_1.4146070
Featured
2024
Conference Publication
Machine learning for prediction of all-cause mortality in acute coronary syndrome
Zaka, A., Gupta, A., Mustafiz, C., Mutahar, D., Parvez, R., Stretton, B., Kovoor, J., Mridha, N. and Bacchi, S. (2024). Machine learning for prediction of all-cause mortality in acute coronary syndrome. ESC Congress 2024, London, United Kingdom, 30 August – 2 September 2024. Oxford, United Kingdom: Oxford University Press. doi: 10.1093/eurheartj/ehae666.3448
Featured
2024
Conference Publication
Artificial Intelligence for the Prediction of All-Cause Mortality and Readmission in Heart Failure: A Meta-Analysis of 558,233 Patients
Zaka, A., Mutahar, D., Mustafiz, C., Gorcilov, J., Abtahi, J., Kamalanathan, H., Tan, S., Hains, L., Sharma, P., Sharma, S., Ragunath, P., Gupta, A., Stretton, B., Kovoor, J., Mridha, N. and Bacchi, S. (2024). Artificial Intelligence for the Prediction of All-Cause Mortality and Readmission in Heart Failure: A Meta-Analysis of 558,233 Patients. 72nd Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand, Perth, WA Australia, 1-4 August 2024. Chatswood, NSW Australia: Elsevier. doi: 10.1016/j.hlc.2024.06.545
Featured
2024
Conference Publication
Machine Learning for Prediction of All-Cause Mortality in Acute Coronary Syndrome
Zaka, A., Gupta, A.K., Mustafiz, C., Mutahar, D., Parvez, R., Stretton, B., Kovoor, J.G., Mridha, N. and Bacchi, S. (2024). Machine Learning for Prediction of All-Cause Mortality in Acute Coronary Syndrome. 72nd Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand, Perth, WA Australia, 1-4 August 2024. Chatswood, NSW Australia: Elsevier. doi: 10.1016/j.hlc.2024.06.566
Featured
2024
Conference Publication
Predictors of Outcomes for Coronary Anomalies Identified Through CT Coronary Angiography Over 10 Years
Lu, Z., Mustafiz, C., Colin, J., Pratap, J., Wahi, S., Challa, P., Coucher, J. and Dahiya, A. (2024). Predictors of Outcomes for Coronary Anomalies Identified Through CT Coronary Angiography Over 10 Years. 72nd Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand, Perth, WA Australia, 1-4 August 2024. Chatswood, NSW Australia: Elsevier. doi: 10.1016/j.hlc.2024.06.178
Featured
2024
Conference Publication
Improving Risk Prediction After Transcatheter Aortic Valve Implantation: A Comparison of Machine Learning With Traditional Methods
Zaka, A., Mutahar, D., Mustafiz, C., Sinhal, S., Gorcilov, J., Evans, S., Gupta, A., Stretton, B., Kovoor, J., Mridha, N., Sivagangabalan, G., Zaman, S., Chow, C., Thiagalingam, A., Kovoor, P. and Bacchi, S. (2024). Improving Risk Prediction After Transcatheter Aortic Valve Implantation: A Comparison of Machine Learning With Traditional Methods. 72nd Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand, Perth, WA Australia, 1-4 August 2024. Chatswood, NSW Australia: Elsevier. doi: 10.1016/j.hlc.2024.06.561
Media
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