营养不良中的人工智能:系统文献综述。

IF 8 1区 医学 Q1 NUTRITION & DIETETICS Advances in Nutrition Pub Date : 2024-09-01 DOI:10.1016/j.advnut.2024.100264
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引用次数: 0

摘要

营养不良是世界人口中经常出现的问题,但对儿童和成人的诊断都不足。有必要开发营养不良筛查和诊断工具,以便及早发现营养不良,防止对患者健康和福祉造成长期并发症。这些工具大多基于预定义问卷和共识指南。人工智能(AI)的使用可使自动工具更早地检测出营养不良,从而预防长期后果。在这项研究中,我们进行了系统的文献综述,目的是提供详细信息,说明正在使用哪些患者群体、筛查工具、机器学习算法、数据类型和变量,以及这些人工智能工具目前的局限性和实施阶段。结果显示,在日常临床实践中,超过 90% 的人工智能模型未被使用,比例之高令人吃惊。此外,监督学习模型似乎是最受欢迎的学习类型。与此同时,与疾病相关的营养不良是所有主要研究分析中发现的最常见的营养不良类别。目前的研究为研究人员提供了一个资源库,帮助他们确定在营养不良中使用人工智能的研究方向。
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Artificial Intelligence in Malnutrition: A Systematic Literature Review

Malnutrition among the population of the world is a frequent yet underdiagnosed problem in both children and adults. Development of malnutrition screening and diagnostic tools for early detection of malnutrition is necessary to prevent long-term complications to patients’ health and well-being. Most of these tools are based on predefined questionnaires and consensus guidelines. The use of artificial intelligence (AI) allows for automated tools to detect malnutrition in an earlier stage to prevent long-term consequences. In this study, a systematic literature review was carried out with the goal of providing detailed information on what patient groups, screening tools, machine learning algorithms, data types, and variables are being used, as well as the current limitations and implementation stage of these AI-based tools. The results showed that a staggering majority exceeding 90% of all AI models go unused in day-to-day clinical practice. Furthermore, supervised learning models seemed to be the most popular type of learning. Alongside this, disease-related malnutrition was the most common category of malnutrition found in the analysis of all primary studies. This research provides a resource for researchers to identify directions for their research on the use of AI in malnutrition.

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来源期刊
Advances in Nutrition
Advances in Nutrition 医学-营养学
CiteScore
17.40
自引率
2.20%
发文量
117
审稿时长
56 days
期刊介绍: Advances in Nutrition (AN/Adv Nutr) publishes focused reviews on pivotal findings and recent research across all domains relevant to nutritional scientists and biomedical researchers. This encompasses nutrition-related research spanning biochemical, molecular, and genetic studies using experimental animal models, domestic animals, and human subjects. The journal also emphasizes clinical nutrition, epidemiology and public health, and nutrition education. Review articles concentrate on recent progress rather than broad historical developments. In addition to review articles, AN includes Perspectives, Letters to the Editor, and supplements. Supplement proposals require pre-approval by the editor before submission. The journal features reports and position papers from the American Society for Nutrition, summaries of major government and foundation reports, and Nutrient Information briefs providing crucial details about dietary requirements, food sources, deficiencies, and other essential nutrient information. All submissions with scientific content undergo peer review by the Editors or their designees prior to acceptance for publication.
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