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Thirty one thank you graphic3/1/2024 During his time, computers were huge, and the cost of increased storage space was astronomical. The origins of AI, specifically machine learning (ML), can be tracked all the way back to the 1950s, when Alan Turing invented the so-called “learning machine” as well as military applications of basic AI 1. In this review, we fill this gap, particularly for physicians in a relatively underexplored area of AI: neonatology. While AI affects daily life enormously, many clinicians may not be aware of how much of the work done with AI technologies may be put into effect in today’s healthcare system. The AI tsunami fueled by advances in artificial intelligence (AI) is constantly changing almost all fields, including healthcare it is challenging to track the changes originated by AI as there is not a single day that AI is not applied to anything new. We also discuss possible directions for new AI models and the future of neonatology with the rising power of AI, suggesting roadmaps for the integration of AI into neonatal intensive care units. In this systematic review, we aimed to further enhance the comprehensiveness of the study. We have categorically summarized 106 research articles from 1996 to 2022 and discussed their pros and cons, respectively. To date, the primary areas of focus in neonatology regarding AI applications have included survival analysis, neuroimaging, analysis of vital parameters and biosignals, and retinopathy of prematurity diagnosis. ![]() We systematically evaluate the roles of both classical machine learning and deep learning in neonatology applications, define the methodologies, including algorithmic developments, and describe the remaining challenges in the assessment of neonatal diseases by using PRISMA 2020 guidelines. Hence, in this paper, we review recently developed machine learning and deep learning-based solutions for neonatology applications. ![]() Although some sub-fields of medicine, such as pediatrics, have been relatively slow in receiving the critical benefits of deep learning, related research in pediatrics has started to accumulate to a significant level, too. The effects of deep learning in medicine have changed the conventional ways of clinical application significantly. Most recent developments in artificial intelligence are coming from deep learning, which has proven revolutionary in almost all fields, from computer vision to health sciences. Machine learning and deep learning are two subsets of artificial intelligence that involve teaching computers to learn and make decisions from any sort of data.
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