肌萎缩侧索硬化
生物标志物
神经科学
生物标志物发现
医学
计算生物学
生物
病理
疾病
蛋白质组学
遗传学
基因
作者
Y. Kitaoka,Toshihiro Uchihashi,Satoshi Kawata,Akira Nishiura,Toru Yamamoto,Shin-ichiro Hiraoka,Yusuke Yokota,Emiko Tanaka Isomura,Mikihiko Kogo,Susumu Tanaka,Igor Spigelman,S Seki
摘要
Neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), present significant challenges owing to their complex pathologies and a lack of curative treatments. Early detection and reliable biomarkers are critical but remain elusive. Artificial intelligence (AI) has emerged as a transformative tool, enabling advancements in biomarker discovery, diagnostic accuracy, and therapeutic development. From optimizing clinical-trial designs to leveraging omics and neuroimaging data, AI facilitates understanding of disease and treatment innovation. Notably, technologies such as AlphaFold and deep learning models have revolutionized proteomics and neuroimaging, offering unprecedented insights into ALS pathophysiology. This review highlights the intersection of AI and ALS, exploring the current state of progress and future therapeutic prospects.
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