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Review
. 2025 Mar 20;15(6):787.
doi: 10.3390/diagnostics15060787.

AI and Smart Devices in Cardio-Oncology: Advancements in Cardiotoxicity Prediction and Cardiovascular Monitoring

Luiza Camelia Nechita  1 , Dana Tutunaru  1 , Aurel Nechita  1 , Andreea Elena Voipan  2 , Daniel Voipan  2 , Ancuta Elena Tupu  1 , Carmina Liana Musat  1
Affiliations
Review

AI and Smart Devices in Cardio-Oncology: Advancements in Cardiotoxicity Prediction and Cardiovascular Monitoring

Luiza Camelia Nechita et al. Diagnostics (Basel). .

Abstract

The increasing prevalence of cardiovascular complications in cancer patients due to cardiotoxic treatments has necessitated advanced monitoring and predictive solutions. Cardio-oncology is an evolving interdisciplinary field that addresses these challenges by integrating artificial intelligence (AI) and smart cardiac devices. This comprehensive review explores the integration of artificial intelligence (AI) and smart cardiac devices in cardio-oncology, highlighting their role in improving cardiovascular risk assessment and the early detection and real-time monitoring of cardiotoxicity. AI-driven techniques, including machine learning (ML) and deep learning (DL), enhance risk stratification, optimize treatment decisions, and support personalized care for oncology patients at cardiovascular risk. Wearable ECG patches, biosensors, and AI-integrated implantable devices enable continuous cardiac surveillance and predictive analytics. While these advancements offer significant potential, challenges such as data standardization, regulatory approvals, and equitable access must be addressed. Further research, clinical validation, and multidisciplinary collaboration are essential to fully integrate AI-driven solutions into cardio-oncology practices and improve patient outcomes.

Keywords: artificial intelligence; cardio-oncology; cardiotoxicity; cardiovascular risk; deep learning; implantable devices; machine learning; real-time monitoring; wearable devices.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Visual roadmap of search strategy and literature selection process.
Figure 2
Figure 2
Roadmap for integrating AI technologies in cardio-oncology for risk assessment and patient monitoring.
See this image and copyright information in PMC

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