Exploration of machine learning techniques in predicting multiple sclerosis disease course Abstract Objective: To explore the value of machine learning methods for predicting multiple sclerosis disease course.
Ensemble machine learning and forecasting can achieve 99% uptime for rural handpumps Abstract: Broken water pumps continue to impede efforts to deliver clean and economically-viable water to the global poor.
Nonparametric Risk Bounds for Time-Series Forecasting Abstract: We derive generalization error bounds for traditional time- series forecasting models.
Machine Learning Methods to Predict Diabetes Complications Abstract: One of the areas where Artificial Intelligence is having more impact is machine learning, which develops algorithms able to learn patterns and decision rules from data.
Predicting Risk of Suicide Attempts Over Time Through Machine Learning Abstract: Traditional approaches to the prediction of suicide attempts have limited the accuracy and scale of risk detection for these dangerous behaviors.
Machine Learning Principles Can Improve Hip Fracture Prediction Abstract: Apply machine learning principles to predict hip fractures and estimate predictor importance in Dual-energy X-ray absorptiometry (DXA)-scanned men and women.
Abstract: The problem of credit risks forecasting is one of the most actively studied issues nowadays, as it is the main risk that commercial bank faced in the management.