甲状腺学中的人工智能:对当前应用,相关挑战和未来方向的叙述性审查
David Toro-Tobon1, Ricardo Loor-Torres1, Mayra Duran1
1Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
概括
人工智能 (AI) 在甲状腺学方面表现有前途,改善了诊断和患者护理. 然而,为了在甲状腺疾病管理中广泛采用人工智能,必须解决有限的验证和数据多样性等挑战.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 内分泌学 在内分泌学.
背景情况:
- 人工智能 (AI) 在医疗保健中的采用正在迅速增加,为生物医学研究和临床应用提供了潜在的好处.
- 甲状腺学中的AI应用旨在提高甲状腺疾病的诊断,治疗,监测和整体医疗保健服务.
研究的目的:
- 为了回顾当前的AI应用在甲状腺学中的景观.
- 确定阻碍人工智能应用的局限性和挑战.
- 探索人工智能在甲状腺疾病管理中的未来方向.
主要方法:
- 人工智能在甲状腺学中的应用文献综述.
- 对目前用于甲状腺结节,甲状腺癌和功能性/自身免疫性甲状腺疾病的AI工具的分析.
- 评估挑战,包括数据限制,验证和临床实用性.
主要成果:
- 人工智能在自动化流程,提高诊断准确度,个性化治疗和帮助甲状腺学临床决策方面取得了有希望的结果.
- 大多数人工智能应用都处于早期验证或临床评估阶段,对风险分层和恶性瘤确定的采用有限.
- 主要挑战包括缺乏前性验证,小型/不多样化的数据集,可解释性问题和不清楚的临床影响.
结论:
- 人工智能具有显著的潜力,可以推进甲状腺学和改善患者的治疗结果.
- 解决目前在验证,数据质量和临床整合方面的局限性对于实现AI在甲状腺疾病护理中的全部价值至关重要.
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