临床营养中的人工智能:数据分析和营养护理的桥梁
Jithinraj Edakkanambeth Varayil1, Suzette J Bielinski2, Manpreet S Mundi3
1Department of Family Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. edakkanambethvarayil.jithinraj@mayo.edu.
Current nutrition reports
|July 3, 2025
概括
人工智能 (AI) 为临床营养挑战提供解决方案,个性化患者干预和增强教育. 人工智能工具可以预测结果并提供实时见解,尽管需要进一步评估.
科学领域:
- 临床营养学 临床营养学
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 营养教育和实践面临着重大挑战.
- 个性化营养干预需要先进的决策支持.
- 在提供实时,基于证据的营养见解方面存在知识差距.
研究的目的:
- 探索人工智能如何推进临床营养.
- 用人工智能解决营养教育和实践中的挑战.
- 突出AI在个性化营养干预和知识传播中的作用.
主要方法:
- 对AI在临床营养中的应用进行审查.
- 在营养结果预测中分析机器学习和自然语言处理.
- 探索用于临床决策支持的生成AI.
主要成果:
- 人工智能在预测营养结果和营养不良等并发症方面表现有前途.
- 人工智能有效地处理大型数据集,以识别风险因素并支持临床医生.
- 人工智能可以个性化教育内容,提高营养概念的可访问性.
结论:
- 人工智能在营养领域有多种潜在应用,包括个性化干预和教育.
- 人工智能可以为医疗保健专业人员提供实时,基于证据的见解.
- 需要进一步的研究来评估AI在营养方面的准确性,可访问性和伦理影响.
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