基于人工智能的2型糖尿病治疗策略的进展:一个关键的更新。

Journal of pharmaceutical analysis Pub Date : 2025-06-01 Epub Date: 2025-04-10 DOI:10.1016/j.jpha.2025.101305
Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari
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摘要

在努力更好地控制2型糖尿病(T2DM)治疗的无情竞争中,本文回顾了最近治疗进展和人工智能(AI)应用的蓬勃发展时代的重大发现之旅。鉴于2型糖尿病的巨大全球负担,改善患者预后的创新治疗方法仍然是公共卫生的优先事项。这篇综述首先对目前的治疗现状进行了深入分析,从新的药物治疗到生活方式干预和新的治疗方法。与此同时,人工智能在糖尿病治疗中的作用也在迅速增加,主要是针对如何通过算法和预测建模来修改和个性化胰岛素治疗。它深入回顾了它们先前存在的协同作用,这有助于了解合作机会将如何开启2型糖尿病护理的未来。通过整合最新的治疗进展和人工智能,总体上展示了更好的筛查、诊断和治疗决策,以预测T2DM的预后,表明了这一关键作用。该综述强调了人工智能在胰岛素治疗中的应用如何在糖尿病护理中具有变革性潜力。这些以人为中心的T2DM管理方法比一些传统策略更有效、更个性化,之所以有效,是因为人工智能算法在诊断标准、预测方法和熟悉的分类工具等领域具有隐藏的协同作用,这些领域具有预后或治疗反应性的相关方面/预测因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update.

In the unrelenting race to strive to dominate type 2 diabetes mellitus (T2DM) care better, this review paper sets out on a significant discovery trip across recent advancements in treatment and the blooming era of artificial intelligence (AI) utilities. Given the considerable global burden of T2DM, innovative therapeutic approaches to improve patient outcomes remain a public health priority. This review first provides an in-depth analysis of the current state of therapy, from novel pharmacotherapy to lifestyle interventions and new treatment methods. At the same time, the rapidly increasing role of AI in diabetes care is woven into the story, mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling. It leaves a deep review of their pre-existing synergies, which helps understand how collaborative opportunities will unlock the future of T2DM care. This critical role is shown by integrating recent therapeutic advances and AI with overall showcasing better screening, diagnosis, and therapeutics decision-making to outcome prediction in T2DM. The review emphasizes how AI applications in insulin therapy have transformative potential in diabetes care. These person-centred approaches to T2DM management, which are more effective and personalized than some traditional strategies, only work because of the often-hidden synergies between AI algorithms in areas such as diagnostic criteria, predictive methods, and familiar classification tools for subgroups with relevant aspects/predictors on prognosis or treatment responsiveness.

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