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在肥胖研究和管理中利用人工智能:全面审查

Sarfuddin Azmi¹, Faisal Kunnathodi¹, Haifa F Alotaibi^1,2

¹Scientific Research Center, Al Hussain bin Ali Street, Ministry of Defense Health Services, Riyadh 12485, Saudi Arabia.

Diagnostics (Basel, Switzerland)

|February 13, 2025

概括

人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 通过实现个性化治疗和风险预测,在肥胖管理方面表现有前途. 需要进一步的研究来应对广泛临床采用的挑战.

科学领域:

医疗信息学医疗信息学
计算生物学计算生物学
公共卫生公共卫生

背景情况:

肥胖是一个复杂的全球健康问题,需要创新的管理策略.
传统的肥胖管理方法在个性化和预测方面存在局限性.
人工智能 (AI) 为分析复杂的健康数据提供了新的工具.

研究的目的:

审查AI,ML和DL在肥胖中的临床和研究应用.
评估AI在识别风险因素,预测结果和个性化肥胖治疗中的作用.
评估人工智能的潜力,以提高对肥胖的医疗保健干预措施.

主要方法:

在PubMed和Google学者的综合文献搜索.
将人工智能研究纳入肥胖研究,管理和治疗干预.
观察性研究,系统性审查和临床应用的审查.

主要成果:

包括ML和DL在内的AI模型用于肥胖预测,患者分层和个性化管理.
人工智能有助于风险预测,早期检测和个性化治疗计划,使用各种数据.
模型的有效性因数据,目标和可解释性而异;性能指标指导选择.

结论:

人工智能为推进个性化和高效的肥胖护理提供了巨大的潜力.
必须解决包括数据质量,伦理和技术要求在内的挑战.
利用人工智能对于肥胖研究和治疗中的精确医疗保健至关重要.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.机器学习是机器学习.肥胖肥胖肥胖肥胖肥胖肥胖肥胖肥胖精准医学是一门精准医学.风险预测风险预测

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