Nature

Predicting cancer risk using machine learning on lifestyle and genetic data

Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. This study investigates the application of ...
Nature

METASPACE-ML: Context-specific metabolite annotation for imaging mass spectrometry using machine learning

Imaging mass spectrometry is a powerful technology enabling spatial metabolomics, yet metabolites can be assigned only to a fraction of the data generated. METASPACE-ML is a machine learning-based ...
ascopubs.org

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...
Visual Studio Magazine

Predicting the Future Using Azure Machine Learning

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
EurekAlert!

CAN-scan: new machine learning (ML) tool predicts drug response in colorectal cancer, opening doors to personalized treatment

A Singaporean research team has developed CAN-Scan (short for Cancer Scan), a next-generation precision oncology platform designed to “scan” the molecular features of each patient’s cancer. Published ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...