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.

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Statisticians from across Europe teamed up to train a competition-predicting, machine learning algorithm. This is what they found.

Six machine learning algorithms—k-nearest neighbors, naive Bayes, multilayer perceptron, random forest, support vector machine, and Extreme Gradient Boosting (XGBoost)—were developed using 10-fold ...

The machine learning algorithm and subsequent simulations are fueled by data, expert knowledge and statistical models ...

A novel machine learning algorithm retrieves remote sensing reflectance (Rrs) from Himawari 8 geostationary data at 10 minute ...

In times past, when we wanted to know which team would win the World Cup, we had to turn to seers with crystal balls, use divination via tea leaves, or hope for Paul the Octopus to tell us what would ...

The primary endpoint was 3-month mortality due to all causes. Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random ...