Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
BERT, XGBoost, and logistic regression models were developed on the training data set before evaluation on the hold-out test data set. The primary outcome was overall classification accuracy for the ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
Abstract: Fake news is spreading more widely as a result of the exponential rise of digital news content, which is a major danger to public trust and democratic societies. This project offers a ...
Objectives To examine primary care contacts among individuals with eating disorders (EDs) and assess differences across ...
Abstract: Class imbalance is a persistent challenge in machine learning, particularly in high-stakes applications such as medical diagnostics, bioinformatics, and fraud detection, where the minority ...
Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random forest [RF], support vector machine [SVM], and k-nearest neighbor ...
Missing a night of sleep leaves a specific chemical signature in saliva that can be reliably detected with a high degree of ...
Department of Biochemistry, Microbiology and Immunology and Ottawa Institute of Systems Biology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario K1H 8M5, Canada ...
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