Artificial intelligence in the management of metabolic disorders: a comprehensive review.

IF 5.4 2区 医学 Q1 Medicine
Aamir Anwar, Simran Rana, Priya Pathak
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引用次数: 0

Abstract

This review explores the significant role of artificial intelligence (AI) in managing metabolic disorders like diabetes, obesity, metabolic dysfunction-associated fatty liver disease (MAFLD), and thyroid dysfunction. AI applications in this context encompass early diagnosis, personalized treatment plans, risk assessment, prevention, and biomarker discovery for early and accurate disease management. This review also delves into techniques involving machine learning (ML), deep learning (DL), natural language processing (NLP), computer vision, and reinforcement learning associated with AI and their application in metabolic disorders. The following study also enlightens the challenges and ethical considerations associated with AI implementation, such as data privacy, model interpretability, and bias mitigation. We have reviewed various AI-based tools utilized for the diagnosis and management of metabolic disorders, such as Idx, Guardian Connect system, and DreaMed for diabetes. Further, the paper emphasizes the potential of AI to revolutionize the management of metabolic disorders through collaborations among clinicians and AI experts, the integration of AI into clinical practice, and the necessity for long-term validation studies. The references provided in the paper cover a range of studies related to AI, ML, personalized medicine, metabolic disorders, and diagnostic tools in healthcare, including research on disease diagnostics, personalized therapy, chronic disease management, and the application of AI in diabetes care and nutrition.

人工智能在代谢性疾病管理中的应用综述
本文探讨了人工智能(AI)在糖尿病、肥胖、代谢功能障碍相关脂肪性肝病(MAFLD)和甲状腺功能障碍等代谢性疾病治疗中的重要作用。人工智能在这方面的应用包括早期诊断、个性化治疗计划、风险评估、预防和生物标志物发现,以实现早期和准确的疾病管理。本文还深入探讨了与人工智能相关的机器学习(ML)、深度学习(DL)、自然语言处理(NLP)、计算机视觉和强化学习等技术及其在代谢紊乱中的应用。以下研究还揭示了与人工智能实施相关的挑战和伦理考虑,例如数据隐私、模型可解释性和偏见缓解。我们回顾了各种用于代谢紊乱诊断和管理的基于人工智能的工具,如Idx、Guardian Connect系统和用于糖尿病的dreams。此外,该论文强调了人工智能的潜力,通过临床医生和人工智能专家之间的合作,人工智能与临床实践的整合,以及长期验证研究的必要性,彻底改变代谢紊乱的管理。本文提供的参考文献涵盖了一系列与人工智能、机器学习、个性化医疗、代谢紊乱和医疗保健诊断工具相关的研究,包括疾病诊断、个性化治疗、慢性病管理以及人工智能在糖尿病护理和营养方面的应用研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Endocrinological Investigation
Journal of Endocrinological Investigation ENDOCRINOLOGY & METABOLISM-
CiteScore
8.10
自引率
7.40%
发文量
242
期刊介绍: The Journal of Endocrinological Investigation is a well-established, e-only endocrine journal founded 36 years ago in 1978. It is the official journal of the Italian Society of Endocrinology (SIE), established in 1964. Other Italian societies in the endocrinology and metabolism field are affiliated to the journal: Italian Society of Andrology and Sexual Medicine, Italian Society of Obesity, Italian Society of Pediatric Endocrinology and Diabetology, Clinical Endocrinologists’ Association, Thyroid Association, Endocrine Surgical Units Association, Italian Society of Pharmacology.
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