Exclaim 发表于 2025-3-30 11:28:28
Hans-Peter Nissenedicting brain age. Remarkably, the relationship between bone and gray matter, as well as the volume of cerebrospinal fluid, were identified as the most pivotal features for precise brain age estimation. To summarize, our proposed methodology exhibits encouraging potential for predicting brain age uNonthreatening 发表于 2025-3-30 13:20:22
http://reply.papertrans.cn/63/6219/621835/621835_52.png放逐某人 发表于 2025-3-30 19:25:55
Hans-Peter Nissenategy to fuse all shape metrics and generate an ensemble classification. We tested the approach in a classification task conducted on 26k participants from the UK Biobank, using body mass index (BMI) thresholds as classification labels (normal vs. obese BMI). Ensemble classification accuracies of 72strdulate 发表于 2025-3-30 23:16:05
Hans-Peter Nissen instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, andexhibit 发表于 2025-3-31 03:00:55
Hans-Peter Nissen we focus on two algorithmic wrapper methods for feature selection that are commonly used in machine learning: Recursive Feature Elimination (RFE), which can be applied regardless of data and model type, as well as Purposeful Variable Selection as described by Hosmer and Lemeshow, specifically for g得体 发表于 2025-3-31 06:42:55
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