| ISSN |
2219-2808 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Pediatrics |
| Manuscript Type |
Minireviews |
| Article Title |
Role of artificial intelligence in congenital heart disease
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Subhrashis Guha Niyogi, Deb Sanjay Nag, Mandar Mahavir Shah, Amlan Swain, Chandrima Naskar, Preeti Srivastava and Ravi Kant |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Deb Sanjay Nag, Department of Anaesthesiology, Tata Main Hospital, C Road West, Northern Town, Bistupur, Jamshedpur 831001, Jharkhand, India. ds.nag@tatasteel.com |
| Key Words |
Heart diseases; Congenital abnormalities; Artificial intelligence; Echocardiography; Diagnosis |
| Core Tip |
Artificial intelligence (AI) offers transformative potential for congenital heart disease (CHD) care, affecting diagnosis, management, and long-term monitoring. This study explores the multifaceted applications of AI across the journey of patients with CHD, highlighting key advancements and critical challenges. Prenatally, AI-enhanced fetal echocardiography and genetic testing promise earlier and more accurate diagnosis, allowing for timely intervention. Postnatally, AI-driven image analysis accelerates diagnosis, and advanced signal processing improves hemodynamic assessment. AI-driven decision support systems tailor treatment strategies based on individual patient characteristics. Long-term care benefits from AI-enabled remote monitoring and wearable technologies, facilitating proactive management and early detection of complications. However, realizing the full potential of AI in CHD requires addressing significant limitations. The development of robust, standardized datasets is crucial for training reliable AI models. Furthermore, ensuring the transparency and explainability of AI algorithms is essential for building trust and accountability. Ethical considerations, including data privacy, bias mitigation, and equitable access, must be carefully addressed. Finally, the seamless integration of AI tools into existing clinical workflows is vital for practical implementation and widespread acceptance. Addressing these challenges will pave the way for AI to revolutionize CHD care, achieve better outcomes, and improve the lives of patients and their families. |
| Publish Date |
2025-06-16 10:38 |
| Citation |
<p>Niyogi SG, Nag DS, Shah MM, Swain A, Naskar C, Srivastava P, Kant R. Role of artificial intelligence in congenital heart disease. <i>World J Clin Pediatr</i> 2025; 14(3): 105926</p> |
| URL |
https://www.wjgnet.com/2219-2808/full/v14/i3/105926.htm |
| DOI |
https://dx.doi.org/10.5409/wjcp.v14.i3.105926 |
