Role of artificial intelligence in congenital heart disease.
Authors
Affiliations (5)
Affiliations (5)
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India.
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India. [email protected].
- Department of Cardiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India.
- Department of Psychiatry, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India.
- Department of Paediatrics, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India.
Abstract
This mini-review explores the transformative potential of artificial intelligence (AI) in improving the diagnosis, management, and long-term care of congenital heart diseases (CHDs). AI offers significant advancements across the spectrum of CHD care, from prenatal screening to postnatal management and long-term monitoring. Using AI algorithms, enhanced fetal echocardiography, and genetic tests improves prenatal diagnosis and risk stratification. Postnatally, AI revolutionizes diagnostic imaging analysis, providing more accurate and efficient identification of CHD subtypes and severity. Compared with traditional methods, advanced signal processing techniques enable a more precise assessment of hemodynamic parameters. AI-driven decision support systems tailor treatment strategies, thereby optimizing therapeutic interventions and predicting patient outcomes with greater accuracy. This personalized approach leads to better clinical outcomes and reduced morbidity. Furthermore, AI-enabled remote monitoring and wearable devices facilitate ongoing surveillance, thereby enabling early detection of complications and provision of prompt interventions. This continuous monitoring is crucial in the immediate postoperative period and throughout the patient's life. Despite the immense potential of AI, challenges remain. These include the need for standardized datasets, the development of transparent and understandable AI algorithms, ethical considerations, and seamless integration into existing clinical workflows. Overcoming these obstacles through collaborative data sharing and responsible implementation will unlock the full potential of AI to improve the lives of patients with CHD, ultimately leading to better patient outcomes and improved quality of life.