首页|Ningbo Medical Center Lihuili Hospital Reports Findings in Alzheimer Disease (Th e application value of Rs-fMRI-based machine learning models for differentiating mild cognitive impairment from Alzheimer’s disease: a systematic review and ... )
Ningbo Medical Center Lihuili Hospital Reports Findings in Alzheimer Disease (Th e application value of Rs-fMRI-based machine learning models for differentiating mild cognitive impairment from Alzheimer’s disease: a systematic review and ... )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Neurodegenerative Dise ases and Conditions - Alzheimer Disease is the subject of a report. According to news reporting originating from Zhejiang, People’s Republic of China, by NewsRx correspondents, research stated, “Various machine learning (ML) models based on restingstate functional MRI (Rs-fMRI) have been developed to facilitate differ ential diagnosis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) . However, the diagnostic accuracy of such models remains understudied.” Financial support for this research came from Zhejiang Traditional Chinese Medic ine Science and Technology Program. Our news editors obtained a quote from the research from Ningbo Medical Center L ihuili Hospital, “Therefore, we conducted this systematic review and meta-analys is to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiat ing MCI from AD. PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis w as conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class clas sification tasks). In total, 23 studies, comprising 5,554 participants were enro lled in the study. In the binary classification tasks (twenty studies), the diag nostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 1.00 ), with a sensitivity of 0.94 (95 %CI: 0.89 0.97) and a specificit y of 0.98 (95%CI: 0.95 1.00). In the multi-class classification t asks (six studies), the diagnostic accuracy of the ML model was 0.98 (95% CI: 0.98 0.99) for NC, 0.96 (95 %CI: 0.96 0.96) for early mild c ognitive impairment (EMCI), 0.97 (95%CI: 0.96 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 0.95) for AD. The Rs-fMRI-based ML model can be adapted to multi-class classification tasks.”
ZhejiangPeople’s Republic of ChinaAs iaAlzheimer DiseaseBrain Diseases and ConditionsCentral Nervous System Dis eases and ConditionsCyborgsDementiaDiagnostics and ScreeningEmerging Tec hnologiesHealth and MedicineMachine LearningNeurodegenerative Diseases and ConditionsTauopathies
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