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

Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore-MIT Alliance, E-04-10, 4 Engineering Drive 3, Singapore, 117576 ...

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 ...

Objective: This study aimed to develop and validate a risk prediction model of 3-month mortality using machine learning (ML) in a large multicenter cohort of patients with anti-MDA5+DM-ILD in China.

Abstract: Support Vector Machines (SVM) are widely used as supervised learning models to solve the classification problem in machine learning. Training SVMs for large datasets is an extremely ...

Abstract: Objective: Since computer-aided diagnosis (CAD) schemes of medical images usually computes large number of image features, which creates a challenge of how to identify a small and optimal ...