arXiv:2006.06418
On mistakes we made in prior Computational Psychiatry Data driven approach projects and how they jeopardize translation of those findings in clinical practice
원문 초록
After performing comparison of the performance of seven different machine learning models on detection depression tasks to show that the choice of features is essential, we compare our methods and results with the published work of other researchers. In the end we summarize optimal practices in order that this useful classification solution can be translated to clinical practice with high accuracy and better acceptance.
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Performing Image Classification for 10 Different Monkey Species using CNN
Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms
Enhanced network anomaly detection based on deep neural networks
ExploreKit: Automatic Feature Generation and Selection
Thumbs up? Sentiment Classification using Machine Learning Techniques
Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives
토론
이 논문과 연결된 포럼 글이 아직 없습니다.