Journal of Rare Cardiovascular Diseases

ISSN: 2299-3711 (Print) e-ISSN: 2300-5505 (Online)

Artificial intelligence and rare cardiovascular diseases: New frontiers in early diagnosis and prognostication

1Assistant Professor, Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh
2Research Scholar, IARCON International LLP
3Physiotherapist, ECHS, Military Hospital, Shimla, Himachal Pradesh
1Assistant Professor, Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh
2Research Scholar, IARCON International LLP
3Physiotherapist, ECHS, Military Hospital, Shimla, Himachal Pradesh
Corresponding Email: dramitsachdeva2410@gmail.com

Full Text:

Abstract

Rare cardiovascular diseases (RCDs) represent a diverse group of conditions that, although individually uncommon, collectively contribute to significant morbidity and mortality. Their diagnosis is often delayed due to heterogeneous presentations, lack of awareness, and limited access to specialized care—challenges that are particularly pronounced in India. Artificial intelligence (AI), encompassing machine learning, deep learning, and natural language processing, has emerged as a transformative tool in cardiovascular medicine, capable of detecting subtle patterns beyond human capacity and integrating multimodal data to enhance early diagnosis and prognostication. This review synthesizes global and India-specific evidence on the application of AI in RCDs. We highlight advances in imaging-based diagnostics, where AI-driven echocardiography, cardiac MRI, and CT angiography improve anomaly detection in hypertrophic cardiomyopathy and congenital heart disease. Genomic and biomarker-based approaches demonstrate how AI can accelerate variant classification and risk prediction in inherited cardiomyopathies and channelopathies. Clinical data integration using electronic health records and natural language processing further enables identification of rare phenotypes and supports decision-making. Beyond diagnosis, AI offers significant promise in prognostication and risk stratification, improving sudden cardiac death prediction, guiding implantable cardioverter-defibrillator (ICD) implantation, and identifying candidates for advanced therapies such as transplantation or gene-based treatments. While challenges persist—including data scarcity, algorithmic bias, infrastructural limitations, and ethical concerns—India’s expanding digital health ecosystem and policies such as the National Rare Disease Policy (2021) and Ayushman Bharat Digital Mission provide unique opportunities. We argue that India is well-positioned to harness AI for RCDs by building multicentric datasets, developing AI-integrated rare disease registries, and fostering multidisciplinary collaboration. With public–private partnerships and global cooperation, India can transform the care of rare cardiovascular diseases, setting a precedent for other resource-limited settings.

key word
artificial intelligence, machine learning, rare cardiovascular diseases, hypertrophic cardiomyopathy, channelopathies, prognostication, precision cardiology, digital health, risk stratification