Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials

IF 6.1 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Current opinion in structural biology Pub Date : 2024-06-04 DOI:10.1016/j.sbi.2024.102857

Francesco Angelucci , Alice Ruixue Ai , Lydia Piendel , Jiri Cerman , Jakub Hort

{"title":"Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials","authors":"Francesco Angelucci , Alice Ruixue Ai , Lydia Piendel , Jiri Cerman , Jakub Hort","doi":"10.1016/j.sbi.2024.102857","DOIUrl":null,"url":null,"abstract":"<div><p>The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these diseases through AI-based analyses of large omics data. The most common neurodegenerative disease, Alzheimer’s disease (AD), is characterized by brain accumulation of specific pathological proteins, accompanied by cognitive impairment. In this review, we summarize the latest progress on the use of AI in different AD-related fields, such as analysis of neuroimaging data enabling early and accurate AD diagnosis; prediction of AD progression, identification of patients at higher risk and evaluation of new treatments; improvement of the evaluation of drug response using AI algorithms to analyze patient clinical and neuroimaging data; the development of personalized AD therapies; and the use of AI-based techniques to improve the quality of daily life of AD patients and their caregivers.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":null,"pages":null},"PeriodicalIF":6.1000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000848/pdfft?md5=eae7764a6735afc1235a469251675644&pid=1-s2.0-S0959440X24000848-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in structural biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959440X24000848","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these diseases through AI-based analyses of large omics data. The most common neurodegenerative disease, Alzheimer’s disease (AD), is characterized by brain accumulation of specific pathological proteins, accompanied by cognitive impairment. In this review, we summarize the latest progress on the use of AI in different AD-related fields, such as analysis of neuroimaging data enabling early and accurate AD diagnosis; prediction of AD progression, identification of patients at higher risk and evaluation of new treatments; improvement of the evaluation of drug response using AI algorithms to analyze patient clinical and neuroimaging data; the development of personalized AD therapies; and the use of AI-based techniques to improve the quality of daily life of AD patients and their caregivers.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

将人工智能融入抗击阿尔茨海默氏症的工作中：诊断、预防、治疗、监测、机制和临床试验

人工智能（AI）在神经病学中的应用是一个不断发展的领域，它为提高复杂神经元疾病的诊断和治疗的准确性提供了机会，并通过基于 AI 的大型 omics 数据分析加深了对这些疾病病因的理解。最常见的神经退行性疾病阿尔茨海默病（AD）的特征是大脑中特定病理蛋白的积累，并伴有认知障碍。在这篇综述中，我们总结了人工智能在不同的阿尔茨海默病相关领域应用的最新进展，如通过分析神经影像学数据实现阿尔茨海默病的早期准确诊断；预测阿尔茨海默病的进展、识别高风险患者并评估新疗法；利用人工智能算法分析患者的临床和神经影像学数据改善药物反应评估；开发个性化的阿尔茨海默病疗法；以及利用基于人工智能的技术改善阿尔茨海默病患者及其护理人员的日常生活质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Current opinion in structural biology 生物-生化与分子生物学

CiteScore

12.20

自引率

2.90%

发文量

179

审稿时长

6-12 weeks

期刊介绍： Current Opinion in Structural Biology (COSB) aims to stimulate scientifically grounded, interdisciplinary, multi-scale debate and exchange of ideas. It contains polished, concise and timely reviews and opinions, with particular emphasis on those articles published in the past two years. In addition to describing recent trends, the authors are encouraged to give their subjective opinion of the topics discussed. In COSB, we help the reader by providing in a systematic manner: 1. The views of experts on current advances in their field in a clear and readable form. 2. Evaluations of the most interesting papers, annotated by experts, from the great wealth of original publications. [...] The subject of Structural Biology is divided into twelve themed sections, each of which is reviewed once a year. Each issue contains two sections, and the amount of space devoted to each section is related to its importance. -Folding and Binding- Nucleic acids and their protein complexes- Macromolecular Machines- Theory and Simulation- Sequences and Topology- New constructs and expression of proteins- Membranes- Engineering and Design- Carbohydrate-protein interactions and glycosylation- Biophysical and molecular biological methods- Multi-protein assemblies in signalling- Catalysis and Regulation