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阿尔茨海默病个性化医疗之路:人工智能的应用

The Road to Personalized Medicine in Alzheimer's Disease: The Use of Artificial Intelligence.

作者信息

Silva-Spínola Anuschka, Baldeiras Inês, Arrais Joel P, Santana Isabel

机构信息

Univ Coimbra, Center for Innovative Biomedicine and Biotechnology, 3004-504 Coimbra, Portugal.

Univ Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.

出版信息

Biomedicines. 2022 Jan 29;10(2):315. doi: 10.3390/biomedicines10020315.

Abstract

Dementia remains an extremely prevalent syndrome among older people and represents a major cause of disability and dependency. Alzheimer's disease (AD) accounts for the majority of dementia cases and stands as the most common neurodegenerative disease. Since age is the major risk factor for AD, the increase in lifespan not only represents a rise in the prevalence but also adds complexity to the diagnosis. Moreover, the lack of disease-modifying therapies highlights another constraint. A shift from a curative to a preventive approach is imminent and we are moving towards the application of personalized medicine where we can shape the best clinical intervention for an individual patient at a given point. This new step in medicine requires the most recent tools and analysis of enormous amounts of data where the application of artificial intelligence (AI) plays a critical role on the depiction of disease-patient dynamics, crucial in reaching early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. In this review, we present an overview of relevant topics regarding the application of AI in AD, detailing the algorithms and their applications in the fields of drug discovery, and biomarkers.

摘要

痴呆症在老年人中仍然是一种极为普遍的综合征,是导致残疾和依赖的主要原因。阿尔茨海默病(AD)占痴呆症病例的大多数,是最常见的神经退行性疾病。由于年龄是AD的主要风险因素,寿命的延长不仅意味着患病率的上升,也增加了诊断的复杂性。此外,缺乏疾病修正疗法凸显了另一个限制因素。从治疗方法向预防方法的转变迫在眉睫,我们正朝着个性化医疗的方向发展,即在特定时间为个体患者制定最佳临床干预措施。医学上的这一新步骤需要最新的工具和对大量数据的分析,其中人工智能(AI)的应用在描绘疾病-患者动态方面起着关键作用,这对于实现早期/最佳诊断、监测和干预至关重要。预测模型和算法是这一创新领域的关键要素。在本综述中,我们概述了AI在AD应用方面的相关主题,详细介绍了算法及其在药物发现和生物标志物领域的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f736/8869403/dbe4c1561d3e/biomedicines-10-00315-g001.jpg

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