Role of artificial intelligence in predicting disease-related malnutrition - A narrative review.

IF 2.5 4区 医学 Q3 BUSINESS Nutricion hospitalaria Pub Date : 2025-01-09 DOI:10.20960/nh.05672
Daniel de Luis Román, Juan José López Gómez, David Emilio Barajas Galindo, Cristina García García
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引用次数: 0

Abstract

Background: disease-related malnutrition (DRM) affects 30-50 % of hospitalized patients and is often underdiagnosed, increasing risks of complications and healthcare costs. Traditional DRM detection has relied on manual methods that lack accuracy and efficiency.

Objective: this narrative review explores how artificial intelligence (AI), specifically machine learning (ML) and deep learning (DL), can transform the prediction and management of DRM in clinical settings.

Methods: we examine widely used ML and DL models, assessing their clinical applicability, advantages, and limitations. The integration of these models into electronic health record systems allows for automated risk detection and optimizes real-time patient management.

Results: ML and DL models show significant potential for accurate assessment of nutritional status and prediction of complications in patients with DRM. These models facilitate improved clinical decision-making and more efficient resource management, although their implementation faces challenges related to the need for large volumes of standardized data and integration with existing systems.

Conclusion: AI offers promising prospects for proactive DRM management, highlighting the need for interdisciplinary collaboration to overcome existing barriers and maximize its positive impact on patient care.

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背景:疾病相关营养不良(DRM)影响 30-50% 的住院病人,而且往往诊断不足,增加了并发症风险和医疗成本。本综述探讨了人工智能(AI),特别是机器学习(ML)和深度学习(DL)如何改变临床环境中 DRM 的预测和管理。方法:我们研究了广泛使用的 ML 和 DL 模型,评估了它们的临床适用性、优势和局限性。将这些模型整合到电子健康记录系统中,可实现自动风险检测,优化实时患者管理:结果:ML 和 DL 模型在准确评估 DRM 患者的营养状况和预测并发症方面显示出巨大的潜力。这些模型有助于改善临床决策和提高资源管理效率,但其实施面临着需要大量标准化数据和与现有系统集成的挑战:人工智能为积极主动的 DRM 管理提供了广阔的前景,同时也强调了跨学科合作的必要性,以克服现有障碍并最大限度地发挥其对患者护理的积极影响。
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来源期刊
Nutricion hospitalaria
Nutricion hospitalaria 医学-营养学
CiteScore
1.90
自引率
8.30%
发文量
181
审稿时长
3-6 weeks
期刊介绍: The journal Nutrición Hospitalaria was born following the SENPE Bulletin (1981-1983) and the SENPE journal (1984-1985). It is the official organ of expression of the Spanish Society of Clinical Nutrition and Metabolism. Throughout its 36 years of existence has been adapting to the rhythms and demands set by the scientific community and the trends of the editorial processes, being its most recent milestone the achievement of Impact Factor (JCR) in 2009. Its content covers the fields of the sciences of nutrition, with special emphasis on nutritional support.
期刊最新文献
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