The application of artificial intelligence in tissue repair and regenerative medicine related to pediatric and congenital heart surgery: a narrative review

Francis, Jeevan, George, Joseph, Peng, Edward and Corno, Antonio F ORCID: https://orcid.org/0000-0003-4374-0992 (2024) The application of artificial intelligence in tissue repair and regenerative medicine related to pediatric and congenital heart surgery: a narrative review. Regenerative Medicine Reports, 1 (2). pp. 131-136. ISSN 3050-6808

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Abstract

Artificial intelligence and machine learning have the potential to revolutionize tissue repair and regenerative medicine in the field of pediatric and congenital heart surgery. Artificial intelligence is increasingly being recognized as a transformative force in healthcare with its ability to analyse large and complex datasets, predict surgical outcomes, and improve surgical education and training with the use of virtual reality and surgical simulators. This review explores the current applications of artificial intelligence in predicting surgical outcomes, improving peri-operative decision-making, and facilitating training for surgeons, particularly in low-income countries. By leveraging advanced algorithms and simulations, artificial intelligence can analyse intricate patient data and anatomical variations, enabling early detection of congenital heart defects and optimising surgical approaches. Ultimately, while barriers such as inconsistent data quality and limited resources remain, the advancement of artificial intelligence technologies offers a promising avenue to enhance regenerative medicine related to patient care and surgical education in pediatric and congenital heart surgery.