模式
计算机科学
人工智能
磁共振成像
认知
认知功能衰退
数据科学
机器学习
心理学
医学
精神科
放射科
病理
痴呆
社会学
疾病
社会科学
作者
Arash Gharehbaghi,Ankica Babić
摘要
This paper presents the results of a scoping review that examines potentials of Artificial Intelligence (AI) in early diagnosis of Cognitive Decline (CD), which is regarded as a key issue in elderly health. The review encompasses peer-reviewed publications from 2020 to 2025, including scientific journals and conference proceedings. Over 70% of the studies rely on using magnetic resonance imaging (MRI) as the input to the AI models, with a high diagnostic accuracy of 98%. Integration of the relevant clinical data and electroencephalograms (EEG) with deep learning methods enhances diagnostic accuracy in the clinical settings. Recent studies have also explored the use of natural language processing models for detecting CD at its early stages, with an accuracy of 75%, exhibiting a high potential to be used in the appropriate pre-clinical environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI