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Sethi Y, Patel N, Kaka N, Desai A, Kaiwan O, Sheth M, Sharma R, Huang H, Chopra H, Khandaker MU, Lashin MMA, Hamd ZY, Emran TB. Artificial Intelligence in Pediatric Cardiology: A Scoping Review. J Clin Med 2022; 11:jcm11237072. [PMID: 36498651 PMCID: PMC9738645 DOI: 10.3390/jcm11237072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 11/22/2022] [Accepted: 11/26/2022] [Indexed: 12/05/2022] Open
Abstract
The evolution of AI and data science has aided in mechanizing several aspects of medical care requiring critical thinking: diagnosis, risk stratification, and management, thus mitigating the burden of physicians and reducing the likelihood of human error. AI modalities have expanded feet to the specialty of pediatric cardiology as well. We conducted a scoping review searching the Scopus, Embase, and PubMed databases covering the recent literature between 2002-2022. We found that the use of neural networks and machine learning has significantly improved the diagnostic value of cardiac magnetic resonance imaging, echocardiograms, computer tomography scans, and electrocardiographs, thus augmenting the clinicians' diagnostic accuracy of pediatric heart diseases. The use of AI-based prediction algorithms in pediatric cardiac surgeries improves postoperative outcomes and prognosis to a great extent. Risk stratification and the prediction of treatment outcomes are feasible using the key clinical findings of each CHD with appropriate computational algorithms. Notably, AI can revolutionize prenatal prediction as well as the diagnosis of CHD using the EMR (electronic medical records) data on maternal risk factors. The use of AI in the diagnostics, risk stratification, and management of CHD in the near future is a promising possibility with current advancements in machine learning and neural networks. However, the challenges posed by the dearth of appropriate algorithms and their nascent nature, limited physician training, fear of over-mechanization, and apprehension of missing the 'human touch' limit the acceptability. Still, AI proposes to aid the clinician tomorrow with precision cardiology, paving a way for extremely efficient human-error-free health care.
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Affiliation(s)
- Yashendra Sethi
- PearResearch, Dehradun 248001, India
- Department of Medicine, Government Doon Medical College, Dehradun 248001, India
| | - Neil Patel
- PearResearch, Dehradun 248001, India
- Department of Medicine, GMERS Medical College, Himmatnagar 383001, India
| | - Nirja Kaka
- PearResearch, Dehradun 248001, India
- Department of Medicine, GMERS Medical College, Himmatnagar 383001, India
| | - Ami Desai
- Department of Medicine, SMIMER Medical College, Surat 395010, India
| | - Oroshay Kaiwan
- PearResearch, Dehradun 248001, India
- Department of Medicine, Northeast Ohio Medical University, Rootstown, OH 44272, USA
- Correspondence: (O.K.); (Z.Y.H.); (T.B.E.)
| | - Mili Sheth
- Department of Medicine, GMERS Gandhinagar, Gandhinagar 382012, India
| | - Rupal Sharma
- Department of Medicine, Government Medical College, Nagpur 440003, India
| | - Helen Huang
- Faculty of Medicine and Health Science, Royal College of Surgeons in Ireland, D02 YN77 Dublin, Ireland
| | - Hitesh Chopra
- Chitkara College of Pharmacy, Chitkara University, Rajpura 140401, India
| | - Mayeen Uddin Khandaker
- Centre for Applied Physics and Radiation Technologies, School of Engineering and Technology, Sunway University, Bandar Sunway 47500, Malaysia
| | - Maha M. A. Lashin
- Department of Biomedical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. 84428, Riyadh 11671, Saudi Arabia
| | - Zuhal Y. Hamd
- Department of Radiological Sciences, College of Health and Rehabilitation Sciences, Princess Nourah bint Abdulrahman University, P.O. 84428, Riyadh 11671, Saudi Arabia
- Correspondence: (O.K.); (Z.Y.H.); (T.B.E.)
| | - Talha Bin Emran
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh
- Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Dhaka 1207, Bangladesh
- Correspondence: (O.K.); (Z.Y.H.); (T.B.E.)
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Morales-Lara C, Adedinsewo DA. Can artificial intelligence improve cardiovascular disease screening in pregnancy? The digital future and cardio-obstetrics. Int J Cardiol 2022; 354:48-49. [DOI: 10.1016/j.ijcard.2022.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 03/06/2022] [Indexed: 11/05/2022]
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