Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Researchers developed a new model to predict the likelihood of critical illness in patients with connective-tissue disease-associated ILD.

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 ...

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 ...

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 ...

Abstract: Recently developed methods for learning sparse classifiers are among the state-of-the-art in supervised learning. These methods learn classifiers that incorporate weighted sums of basis ...