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• W4312201445 abstract "Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment." @default.
• W4312201445 created "2023-01-04" @default.
• W4312201445 creator A5032209991 @default.
• W4312201445 creator A5080884423 @default.
• W4312201445 date "2022-12-26" @default.
• W4312201445 modified "2023-10-14" @default.
• W4312201445 title "Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach" @default.
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• W4312201445 doi "https://doi.org/10.3390/cells12010102" @default.
• W4312201445 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36611896" @default.
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