人工智能与甲状腺疾病管理：甲状腺功能检测的考虑因素。
Artificial intelligence and thyroid disease management: considerations for thyroid function tests.
机构信息
Department of Clinical Biochemistry, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium.
Department of Biochemistry, Pant Institute of Postgraduate Medical Education & Research, Delhi, India.
出版信息
Biochem Med (Zagreb). 2022 Jun 15;32(2):020601. doi: 10.11613/BM.2022.020601.
Artificial intelligence (AI) is transforming healthcare and offers new tools in clinical research, personalized medicine, and medical diagnostics. Thyroid function tests represent an important asset for physicians in the diagnosis and monitoring of pathologies. Artificial intelligence tools can clearly assist physicians and specialists in laboratory medicine to optimize test prescription, tests interpretation, decision making, process optimization, and assay design. Our article is reviewing several of these aspects. As thyroid AI models rely on large data sets, which often requires distributed learning from multi-center contributions, this article also briefly discusses this issue.
人工智能（AI）正在改变医疗保健领域，为临床研究、个性化医疗和医学诊断提供新工具。甲状腺功能测试是医生在诊断和监测疾病方面的重要工具。人工智能工具可以为医生和医学检验专家提供帮助，优化检验方案、检验解读、决策制定、流程优化和检测设计。本文综述了其中的几个方面。由于甲状腺 AI 模型依赖于大型数据集，这通常需要通过多中心贡献进行分布式学习，本文还简要讨论了这个问题。
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