New machine-learning models capture the rapid evolution of antimicrobial resistance

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...
Analytics Insight

Data Science: Building Machine Learning Models, Harvard University

Harvard University presents its eight-week online course through edX, which imparts to students essential knowledge of ...

A urine-based biological aging clock: Machine learning and microRNA offer accurate prediction

Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...
Chromatography Online

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

Data bias reduces reliability of AI models predicting antimicrobial resistance

Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...
ascopubs.org

Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence

Assessment of Circulating Tumor DNA Burden in Patients With Metastatic Gastric Cancer Using Real-World Data Endometrial cancer (EC) is the most common gynecologic cancer in the United States with ...

Machine learning offers growers a new tool for predicting crop water use

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant ...
Risk.net

Volume 20, Number 1 (March 2026)

This issue of The Journal of Risk Model Validation features two papers that directly address validation using machine learning. Whether their findings imply we will all (including the editor) become ...
The American Journal of Managed Care

New 9-Gene Classifier May More Accurately Predict Metastasis Across STS, Other Cancers

Producing the highest accuracy, the 9-gene set produced became the basis of the final classifier. When applied to multiple STS datasets, the model consistently separated patients into low-risk and ...