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Review
. 2025 Feb 19;27(1):56.
doi: 10.1007/s11886-025-02215-w.

Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review

Avirup Guha #  1   2 , Viraj Shah #  3   4 , Tarek Nahle  3   4 , Shivam Singh  5 , Harikrishnan Hyma Kunhiraman  3   4 , Fathima Shehnaz  6 , Priyanshu Nain  7 , Omar M Makram  3   4 , Morteza Mahmoudi  8 , Sadeer Al-Kindi  9 , Anant Madabhushi  10 , Rakesh Shiradkar  11 , Hisham Daoud  12
Affiliations
Review

Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review

Avirup Guha et al. Curr Cardiol Rep. .

Abstract

Purpose of review: This review explores the role of artificial intelligence (AI) in cardio-oncology, focusing on its latest application across problems in diagnosis, prognosis, risk stratification, and management of cardiovascular (CV) complications in cancer patients. It also highlights multi-omics analysis, explainable AI, and real-time decision-making, while addressing challenges like data heterogeneity and ethical concerns.

Recent findings: AI can advance cardio-oncology by leveraging imaging, electronic health records (EHRs), electrocardiograms (ECG), and multi-omics data for early cardiotoxicity detection, stratification and long-term risk prediction. Novel AI-ECG models and imaging techniques improve diagnostic accuracy, while multi-omics analysis identifies biomarkers for personalized treatment. However, significant barriers, including data heterogeneity, lack of transparency, and regulatory challenges, hinder widespread adoption. AI significantly enhances early detection and intervention in cardio-oncology. Future efforts should address the impact of AI technologies on clinical outcomes, and ethical challenges, to enable broader clinical adoption and improve patient care.

Keywords: Artificial intelligence; Cardio-oncology; Cardiotoxicity; Deep learning; Machine learning; Personalized medicine.

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Conflict of interest statement

Declarations. Human and Animal Rights and Informed Consent: This article does not contain any studies with human or animal subjects performed by any of the authors. Competing Interests: Avirup Guha discloses the following: (1) consulting fees from Pfizer, Novartis, and Myovant; and (2) ZERO Prostate Cancer – health equity task force, and Doctorpedia – founding medical partner.Morteza Mahmoudi discloses that (1) he is a co-founder and director of the Academic Parity Movement (www.paritymovement.org), a non-profit organization dedicated to addressing academic discrimination, violence and incivility; (2) he is a co-founder of Targets’ Tip and Albuderm; and (3) he receives royalties/honoraria for his published books, plenary lectures, and licensed patents.Sadeer Al-Kindi discloses the following: (1) grants or contracts from Ionis Pharmaceuticals and the National Institutes of Health; and (2) consulting fees from Heartflow Inc.; (3) Member of the AirPressureNYC trial; and (4) Patents planned, issued, or pending for: DEEP-LEARNING-BASED HEPATIC FAT ASSESSMENT, Major adverse cardiovascular event risk prediction based on comprehensive analysis of ct calcium score exam, Prediction of major adverse cardiovascular events (mace) from a.i. analysis of pericoronary fat in CT images, Prediction of stent expansion using finite element modeling and machine learning, and Prediction of stent expansion for treatments.Anant Madabhushi disclosures the following: (1) two different R01 grants with Inspirata Inc.; (2) licenses to Picture Health and Elucid Bioimaging; (3) consulting fees from Takeda Inc.; (4) Frederick National Laboratory Advisory Committee – member; (5) Advisory board of Picture Health and SimBioSys; (6) Stock or stock options for Picture Health, Elucid Bioimaging, and Inspirata Inc.; and (7) Sponsored research agreements with AstraZeneca and Bristol Myers Squibb.The other authors declare that they have no conflict of interest.

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