Machine learning can predict patients' responses to antidepressants while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Healio

Researchers create AI model to predict sepsis in pediatric EDs

Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

BioMark Diagnostics Announces Publication of Peer-Reviewed Validation of Machine Learning Models for Lung Cancer Detection in Frontiers in Oncology

Advancing Superior Accuracy in Early Lung Cancer Detection Using Selective Metabolic Pathways and Data Enrichment for ...
Government Technology

Using Machine Learning to Understand College Closures

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...
ascopubs.org

Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
PharmTech

Integrating AI and Machine Learning in Drug Discovery and Development

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...
Eureka

Keysight Unveils Machine Learning Toolkit for Semiconductor Modelling

Keysight Technologies has launched a new Machine Learning Toolkit within its Device Modelling Software Suite, designed to ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...