Medical Xpress

Integrating machine learning with statistical methods enhances disease risk prediction models

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

I Don't Understand Ridge Regression! Learning from Linear Regression with Manual Calculations

While doing machine learning, I learned that there is a machine learning method called ridge regression. I feel like I understand it somewhat, but it also feels like I don't really get it. Therefore, ...
techtarget

Regression in machine learning: A crash course for engineers

Finding relationships among data is an important skill for any business professional. Understanding cause-and-effect relationships can be the critical factor when it comes to wasted time, lost profits ...
BIOENGINEER

Machine Learning Outperforms Design Codes at Predicting Concrete Crack Spacing

Extremely randomized trees models trained on 96 experimental records predicted primary crack spacing in reinforced concrete ...
GitHub

Used Car Price Prediction Using Machine Learning Regression

Used car price prediction using Machine Learning regression algorithms and Random Forest. - KunalGupta9321/Used-Car-Price-Prediction ...
Medical Xpress

Regression approach outperforms ML algorithms in predicting optimal surgical method in submucosal tumor patients

Submucosal tumors (SMTs) are usually found in the stomach and esophagus during an upper endoscopy. Submucosal tunneling endoscopic resection (STER) and non-tunneling endoscopic resection (NTER) are ...
BIOENGINEER

Machine learning predicts late-onset PICU infection risk in retrospective cohort

A retrospective study of 1,012 children found that XGBoost predicted late-onset PICU infection risk with a test-set AUC of ...
Science Daily

Researchers develop new machine learning method for modeling of chemical reactions

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...