ReviewFrontiers in digital health2023
Role of artificial intelligence in early detection of congenital heart diseases in neonates.
Review in Frontiers in digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Congenital heart disease diagnosis using machine learning: a systematic literature review.Frontiers in medicine · 2026Pooled it
- Delayed Diagnosis of Congenital Heart Diseases in Adults: Opportunities for Improving Diagnostic Strategies.Journal of cardiovascular development and disease · 2026Review
- [Clinical value of AI-assisted cardiac auscultation in screening for congenital heart disease in neonates].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026Article
- Artificial I ntelligence-Assisted Fetal Echocardiography: Improving Early Detection and Neonatal Outcomes of Congenital Heart Disease.Cardiology and cardiovascular medicine · 2026Article
- Pediatrics 4.0: the Transformative Impacts of the Latest Industrial Revolution on Pediatrics.Health care analysis : HCA : journal of health philosophy and policy · 2025Article
- Prospective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates.International journal of general medicine · 2025Review
- Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects.Frontiers in pediatrics · 2025Review
- Machine learning-based prediction of hemodynamically significant patent ductus arteriosus in preterm neonates: a pioneering insight.Frontiers in pediatrics · 2025Article
- Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.BMC pregnancy and childbirth · 2024Article
- How Will Artificial Intelligence Shape the Future of Decision-Making in Congenital Heart Disease?Journal of clinical medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the domain of healthcare, most importantly pediatric healthcare, the role of artificial intelligence (AI) has significantly impacted the medical field. Congenital heart diseases represent a group of heart diseases that are known to be some of the most critical cardiac conditions present at birth. These heart diseases need a swift diagnosis as well as an intervention to ensure the wellbeing of newborns. Fortunately, with the help of AI, including the highly advanced algorithms, analytics and imaging involved, it provides us with a promising era for neonatal care. This article reviewed published data in PubMed, Science Direct, UpToDate, and Google Scholar between the years 2015-2023. To conclude The use of artificial intelligence in detecting congenital heart diseases has shown great promise in improving the accuracy and efficiency of diagnosis. Several studies have demonstrated the efficacy of AI-based approaches for diagnosing congenital heart diseases, with results indicating that the systems can achieve high levels of sensitivity and specificity. In addition, AI can help reduce the workload of healthcare professionals allowing them to focus on other critical aspects of patient care. Despite the potential benefits of using AI, in addition to detecting congenital heart disease, there are still some challenges to overcome, such as the need for large amounts of high-quality data and the requirement for careful validation of the algorithms. Nevertheless, with ongoing research and development, AI is likely to become an increasingly valuable tool for improving the diagnosis and treatment of congenital heart diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.