A longitudinal machine-learning approach to predicting nursing home closures in the U.S.
Our study demonstrates that U.S. nursing home closures, while relatively rare events (approximately 5% of facilities over the past decade),...
predicting
Evaluation of various traditional machine learning techniques for predicting the acute effect of different hamstring muscle stretching methods among male soccer players
Hosseini, E., Alimoradi, M., Iranmanesh, M., Saki, F. & Konrad, A. The effects of 8 weeks of dynamic hamstring stretching...
Explainable machine learning methods for predicting electricity consumption in a long distance crude oil pipeline
Evaluation of predictive performanceTo evaluate the predictive performance of the proposed hybrid model, the GS-XGBoost hybrid model was compared with...
Predicting drug solubility in supercritical carbon dioxide green solvent using machine learning models based on thermodynamic properties
Bai, T., Kobayashi, K., Tamura, K., Jun, Y. & Zheng, L. Supercritical CO2 dyeing for nylon, acrylic, polyester, and casein...
Predicting Oral Bioavailability via Transfer Learning Techniques
In the realm of pharmacology and drug discovery, the quest for high oral bioavailability remains one of the most significant...
A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs
Patient demographics and baseline characteristicsIn this study, we initially included 4344 patients from the Bioreg dataset. After applying inclusion criteria...
