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Detection of formal thought disorders in child and adolescent psychosis using machine learning and neuropsychometric data
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Detection of formal thought disorders in child and adolescent psychosis using machine learning and neuropsychometric data
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"A range of machine learning models (Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)) were employed to classify participants into FTD-positive and FTD-negative groups based on these neuropsychological measures and their antipsychotic regimen (medication load in chlorpromazine equivalents)."
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"Table 2 Hyperparameter tuning of the machine learning models."
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Vector Laboratories is a leading provider of labeling and detection reagents that enable scientists to precisely visualize and study tissues and cells in the immunohistochemistry, immunofluorescence, and glycobiology space. For over 40 years, they have been helping scientists make breakthroughs faster by providing the highest quality reagents and scientific support. As pioneers in the art of scientific discovery, their VECTASTAIN ABC kits, VECTASHIELD mounting media, ImmPRESS Polymer reagents and unique lectins have aided researchers to address important targets in critical biological pathways.