Advancing Neurological Disease Prediction through Machine Learning Techniques

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...
Medscape

Advanced Machine Learning Model Predicts Onset of Epilepsy and Depression

A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Medical Xpress

Machine learning models identify key predictors of driving under the influence of alcohol or cannabis

The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary factors contributing to driving under the influence, according to a new analysis ...
ascopubs.org

Real-world predictors of adverse clinical outcomes in pancreatic cancer using a machine-learning framework.

Machine learning and statistical prediction of overall survival (OS) from pre-dose plasma biomarkers in a randomized phase 2 trial (1801 Part 3B) of the GSK-3 inhibitor elraglusib in metastatic ...
Healio

Electronic health record-based machine learning models improve OSA prediction

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
ascopubs.org

Gastric Cancer Mortality-to-Incidence Ratios in Latin America and the Caribbean: A Machine Learning Analysis of Socioeconomic and Clinical Research Predictors

We conducted a retrospective, country-level study integrating GLOBOCAN 2022 incidence and mortality data, ClinicalTrials.gov records (2004-2025), and socioeconomic indicators (United Nations ...
Open Access Government

Basic machine learning with lessR : Easy, simple, and free

David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...
Frontiers

Hybrid Hydroinformatics: Integrating Machine Learning and Process-Based Modeling for Climate-Resilient Water Systems

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...