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. 2024 Jan 7;28(2):74-86.
doi: 10.14744/AnatolJCardiol.2023.3685. Online ahead of print.

Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases

Affiliations

Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases

Serdar Bozyel et al. Anatol J Cardiol. .

Abstract

Despite all the advancements in science, medical knowledge, healthcare, and the healthcare industry, cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The main reasons are the inadequacy of preventive health services and delays in diagnosis due to the increasing population, the failure of physicians to apply guide-based treatments, the lack of continuous patient follow-up, and the low compliance of patients with doctors' recommendations. Artificial intelligence (AI)-based clinical decision support systems (CDSSs) are systems that support complex decision-making processes by using AI techniques such as data analysis, foresight, and optimization. Artificial intelligence-based CDSSs play an important role in patient care by providing more accurate and personalized information to healthcare professionals in risk assessment, diagnosis, treatment optimization, and monitoring and early warning of CVD. These are just some examples, and the use of AI for CVD decision support systems is rapidly evolving. However, for these systems to be fully reliable and effective, they need to be trained with accurate data and carefully evaluated by medical professionals.

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Conflict of interest statement

Declaration of Interests: The authors have no conflict of interest to declare.

Figures

Figure 1.
Figure 1.
Clinical decision support systems for cardiovascular risk assessment and management.

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References

    1. Groenhof TKJ, Asselbergs FW, Groenwold RHH, et al. The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis. BMC Med Inform Decis Mak. 2019;19(1):108. (10.1186/s12911-019-0824-x) - DOI - PMC - PubMed
    1. Njie GJ, Proia KK, Thota AB, et al. Clinical decision support systems and prevention: a community guide cardiovascular disease systematic review. Am J Prev Med. 2015;49(5):784 795. (10.1016/j.amepre.2015.04.006) - DOI - PMC - PubMed
    1. Wells S, Furness S, Rafter N, et al. Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice. Eur J Cardiovasc Prev Rehabil. 2008;15(2):173 178. (10.1097/HJR.0b013e3282f13af4) - DOI - PubMed
    1. Groenhof TKJ, Rittersma ZH, Bots ML, et al. A computerised decision support system for cardiovascular risk management ‘live’ in the electronic health record environment: development, validation and implementation-the Utrecht cardiovascular Cohort Initiative. Neth Heart J. 2019;27(9):435 442. (10.1007/s12471-019-01308-w) - DOI - PMC - PubMed
    1. HYP Hastalık Yönetim Platformu. Accessed 26.11.2022.

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