Bridging gaps in AI-driven cardio-oncology: global advances and Middle East perspectives

Cardiotoxicity remains a critical barrier to effective cancer treatment, contributing significantly to morbidity and mortality in cancer survivors. Recent advancements (2020-2025) highlight artificial intelligence (AI) as a transformative tool in cardio-oncology, enhancing cardiotoxicity detection, personalized risk assessment, and patient management. Despite rapid technological progress, significant gaps remain in AI integration across different healthcare settings globally.

This narrative review systematically synthesizes literature published between 2020 and 2025, evaluating key applications of AI in cardio-oncology, including imaging modalities, predictive modeling, wearable technology, and clinical decision-support systems. Comparative analyses between high-income countries (HICs) and low-to-middle-income countries (LMICs), with an emphasis on the Middle East, were performed to illustrate global disparities and unique regional challenges.

AI-enabled imaging technologies, particularly echocardiography and cardiac MRI, significantly improved the early detection and management of cardiotoxicity. Predictive algorithms integrating multimodal data demonstrated superior risk stratification accuracy over traditional methods. Wearable technologies combined with AI enabled real-time cardiac monitoring, demonstrating feasibility in diverse resource settings. Nonetheless, adoption barriers such as dataset biases, inadequate regulatory frameworks, prohibitive costs, ethical dilemmas, and limited digital infrastructure persist, disproportionately affecting LMICs.

To harness the full potential of AI in cardio-oncology, strategic investments in collaborative international research, standardized regulatory frameworks, educational initiatives, and infrastructural support are urgently needed. Future research should prioritize equitable, inclusive AI solutions, validated through prospective trials and adapted specifically to underserved populations.