{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T08:03:59Z","timestamp":1784016239815,"version":"3.55.0"},"reference-count":117,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Paediatrics Child Health"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) is becoming an integral tool in clinical care. The recent position statement by the Royal Australasian College of Physicians (RACP) provides a timely practical blueprint on implementing and monitoring the use of AI in clinical practice. Although the data\u2010rich environment of NICU presents a good setting for evaluation of AI\u2010assisted clinical application, research on AI in Neonatology is relatively sparse compared to other fields in medicine. In this narrative overview, we summarised published research on AI in neonatology identified through a PubMed search to 29 December 2025, including early forms of AI\/machine learning technologies in the 1990s to the more recent deep learning and large language model approaches across a broad range of conditions and functions. Our overview reveals a highly fragmented evidence landscape with the vast majority of published literature grouped around a few conditions, chiefly retinopathy of prematurity characterisation, neonatal seizure detection and neurodevelopmental outcome prediction, with very few studies in other areas. Most studies are single\u2010centre, retrospective and preliminary, without any external validation. A small number of \u2018near\u2010deployment\u2019 technologies, including automated oxygen control, the ANSeR seizure\u2010detection algorithm, AI\u2010based retinopathy of prematurity screening and automated General Movements Assessment for cerebral palsy screening, are notable exceptions. Rigorous clinical trials on AI\u2010assisted therapy, diagnosis or prognostication, followed by implementation studies evaluating workflow integration across diverse geographical and socioeconomic settings are needed to address this critical translation\u2010to\u2010practice gap. Anticipated challenges specific to neonatology include methodological issues such as shifting physiological benchmarks across gestational ages and imperfect reference standards, as well as ethical issues such as establishing consent frameworks for long\u2010term data use in a vulnerable population. Challenges shared with other fields in medicine include ensuring equitable applicability of AI across diverse populations with differing characteristics and resources and maintaining transparency in AI model development and deployment.<\/jats:p>","DOI":"10.1111\/jpc.70489","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T07:09:52Z","timestamp":1784012992000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence in Neonatal Care: The Breadth of Promise, the Depth of Challenge\u2014An Overview"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4204-3098","authenticated-orcid":false,"given":"N. M.","family":"Lai","sequence":"first","affiliation":[{"name":"Faculty of Health and Medical Sciences, School of Medicine Taylor's University  Subang Jaya Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K. T.","family":"Yeo","sequence":"additional","affiliation":[{"name":"Department of Neonatology KK Women's and Children's Hospital  Singapore Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Y.","family":"Kong","sequence":"additional","affiliation":[{"name":"Department of Neonatology KK Women's and Children's Hospital  Singapore Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4306-2933","authenticated-orcid":false,"given":"M. E.","family":"Abdel\u2010Latif","sequence":"additional","affiliation":[{"name":"Discipline of Neonatology, School of Medicine and Psychology, College of Science and Medicine Australian National University  Canberra ACT Australia"},{"name":"Department of Neonatology, Centenary Hospital for Women and Children Canberra Hospital  Canberra ACT Australia"},{"name":"Department of Public Health, College of Science, Health and Engineering La Trobe University  Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"e_1_2_9_2_1","volume-title":"Artificial Intelligence\u2010Enabled Medical Devices","author":"FDA","year":"2026"},{"issue":"7788","key":"e_1_2_9_3_1","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1038\/s41586-019-1799-6","article-title":"International Evaluation of an AI System for Breast Cancer Screening","volume":"577","author":"McKinney S. M.","year":"2020","journal-title":"Nature"},{"key":"e_1_2_9_4_1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/s41746-018-0029-1","article-title":"Scalable and Accurate Deep Learning With Electronic Health Records","volume":"1","author":"Rajkomar A.","year":"2018","journal-title":"NPJ Digital Medicine"},{"issue":"1","key":"e_1_2_9_5_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41372-023-01848-5","article-title":"Transforming Neonatal Care With Artificial Intelligence: Challenges, Ethical Consideration, and Opportunities","volume":"44","author":"Sullivan B. A.","year":"2024","journal-title":"Journal of Perinatology : Official Journal of the California Perinatal Association"},{"key":"e_1_2_9_6_1","doi-asserted-by":"crossref","DOI":"10.2196\/63175","article-title":"Opportunities and Challenges of Using Artificial Intelligence in Predicting Clinical Outcomes and Length of Stay in Neonatal Intensive Care Units: Systematic Review","volume":"27","author":"Tudor S.","year":"2025","journal-title":"Journal of Medical Internet Research"},{"issue":"10409","key":"e_1_2_9_7_1","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1016\/S0140-6736(23)00878-4","article-title":"National, Regional, and Global Estimates of Preterm Birth in 2020, With Trends From 2010: A Systematic Analysis","volume":"402","author":"Ohuma E. O.","year":"2023","journal-title":"Lancet (London, England)"},{"issue":"2","key":"e_1_2_9_8_1","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/S2352-4642(21)00311-4","article-title":"Global, Regional, and National Causes of Under\u20105 Mortality in 2000\u201319: An Updated Systematic Analysis With Implications for the Sustainable Development Goals","volume":"6","author":"Perin J.","year":"2022","journal-title":"Lancet Child and Adolescent Health"},{"key":"e_1_2_9_9_1","volume-title":"Using Artificial Intelligence in Clinical Practice: Position Statement","author":"RACP","year":"2026"},{"issue":"1","key":"e_1_2_9_10_1","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1038\/s41746-023-00941-5","article-title":"The Past, Current, and Future of Neonatal Intensive Care Units With Artificial Intelligence: A Systematic Review","volume":"6","author":"Keles E.","year":"2023","journal-title":"NPJ Digital Medicine"},{"issue":"12","key":"e_1_2_9_11_1","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1038\/s41372-022-01392-8","article-title":"Predicting Clinical Outcomes Using Artificial Intelligence and Machine Learning in Neonatal Intensive Care Units: A Systematic Review","volume":"42","author":"RM M. A.","year":"2022","journal-title":"Journal of Perinatology"},{"issue":"1","key":"e_1_2_9_12_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.siny.2025.101690","article-title":"A Systematic Review on the Use of Artificial Intelligence in the Neonatal Intensive Care Unit: Far Beyond the Potential Impact","volume":"31","author":"Millana A. M.","year":"2026","journal-title":"Seminars in Fetal and Neonatal Medicine"},{"issue":"2","key":"e_1_2_9_13_1","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1038\/s41390-024-03774-4","article-title":"AI Models in Clinical Neonatology: A Review of Modeling Approaches and a Consensus Proposal for Standardized Reporting of Model Performance","volume":"98","author":"Husain A.","year":"2025","journal-title":"Pediatric Research"},{"issue":"8","key":"e_1_2_9_14_1","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","article-title":"Large Language Models in Medicine","volume":"29","author":"Thirunavukarasu A. 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