A review of risk prediction models in cardiovascular disease: conventional approach vs. artificial intelligent approach
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide and is a global health issue. Traditionally, statistical models are used commonly in the risk prediction and assessment of CVD. However, the adoption of artificial intelligent (AI) approach is rapidly taking hold in the current era of technology to evaluate patient risks and predict the outcome of CVD. In this review, we outline various conventional risk scores and prediction models and do a comparison with the AI approach. The strengths and limitations of both conventional and AI approaches are discussed. Besides that, biomarker discovery related to CVD are also elucidated as the biomarkers can be used in the risk stratification as well as early detection of the disease. Moreover, problems and challenges involved in current CVD studies are explored. Lastly, future prospects of CVD risk prediction and assessment in the multi-modality of big data integrative approaches are proposed.
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Traditional risk calculators often provide generalized risk assessments based on standard biomarkers but may not account for the complexity of individual risk profiles.
“Traditional risk calculators often provide generalized risk assessments based on standard biomarkers (e.g., cholesterol levels, blood pressure) but may not account for the complexity of individual risk profiles (99).”
From Generative artificial intelligence in predictive analysis of diabetes and its complications: a narrative review (2025) · cites this paper as [99]
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- Authors
- Mohd Faizal, A. S., Thevarajah, T. M., Khor, S. M., & Chang, S.-W.
- Affiliations
- University of Malaya (MY)
- Corresponding author
- Chang, Siow-Wee
- Venue
- Computer Methods and Programs in Biomedicine
- Publisher
- Elsevier BV
- Published
- 2021-08
- Volume
- 207
- Pages
- 106190
- ISSN
- 0169-2607 (ISSN-L)
- OpenAlex
- W3164598001
- Cited by
- 113
- References
- 7
- Citations by year
- 2026: 16 · 2025: 40 · 2024: 23 · 2023: 20 · 2022: 12 · 2021: 2
- FWCI
- 12.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer Methods and Programs in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Universiti Malaya (IIRG020B-2019)
- Topics
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- cardiovascular disease, cardiovascular risk prediction, risk score, artificial intelligence, machine learning, biomarkers, risk stratification, early detection, big data integration, multi-omics
- MeSH terms
- Big Data, Artificial Intelligence, Cardiovascular Diseases, Humans, Risk Factors
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