培育明天:将人工智能与社会儿科学相结合,促进儿童的全面福祉。

IF 1.3 Q3 PEDIATRICS
Murat Gülşen, Sıddıka Songül Yalçın
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引用次数: 0

摘要

这篇综合评论探讨了人工智能(AI)与社会儿科领域的结合,强调了人工智能彻底改变儿童医疗保健的潜力。社会儿科学是该学科的一个专业分支,重点关注社会、环境和经济因素对儿童健康和发展的重大影响。该领域采用综合方法,将医学、心理学和环境因素融为一体。本综述旨在从社会儿科学的角度探讨人工智能在革新儿童医疗保健方面的潜力。为此,我们探讨了人工智能在预防保健、生长监测、营养指导、环境风险因素预测和虐待儿童早期检测方面的应用。研究结果凸显了人工智能在社会儿科各个领域的重要贡献。人工智能在处理大型数据集方面的熟练程度表明,它可以增强诊断过程、个性化治疗和改善整体医疗保健管理。在预防保健、生长监测、营养咨询、环境风险预测和早期儿童虐待检测等方面都取得了显著进步。我们发现,将人工智能融入社会儿科医疗保健旨在提高儿科医疗服务的有效性、可及性和公平性。这种整合可确保为每个儿童提供高质量的医疗服务,无论其社会背景如何。这项研究阐明了人工智能在社会儿科领域的多方面应用,包括自然语言处理、用于健康结果预测的机器学习算法,以及用于健康和环境监测的人工智能驱动工具,共同促进建立一个更高效、更知情、反应更迅速的儿科医疗保健系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fostering Tomorrow: Uniting Artificial Intelligence and Social Pediatrics for Comprehensive Child Well-being.

This comprehensive review explores the integration of artificial intelligence (AI) in the field of social pediatrics, emphasizing its potential to revolutionize child healthcare. Social pediatrics, a specialized branch within the discipline, focuses on the significant influence of societal, environmental, and economic factors on children's health and development. This field adopts a holistic approach, integrating medical, psychological, and environmental considerations. This review aims to explore the potential of AI in revolutionizing child healthcare from social pediatrics perspective. To achieve that, we explored AI applications in preventive care, growth monitoring, nutritional guidance, environmental risk factor prediction, and early detection of child abuse. The findings highlight AI's significant contributions in various areas of social pediatrics. Artificial intelligence's proficiency in handling large datasets is shown to enhance diagnostic processes, personalize treatments, and improve overall healthcare management. Notable advancements are observed in preventive care, growth monitoring, nutritional counseling, predicting environmental risks, and early child abuse detection. We find that integrating AI into social pediatric healthcare aims to enhance the effectiveness, accessibility, and equity of pediatric health services. This integration ensures high-quality care for every child, regardless of their social background. The study elucidates AI's multifaceted applications in social pediatrics, including natural language processing, machine learning algorithms for health outcome predictions, and AI-driven tools for health and environmental monitoring, collectively fostering a more efficient, informed, and responsive pediatric healthcare system.

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