How open science and shared data can help tackle global challenges: The Crete Declaration

The global community is facing a number of urgent challenges, such as emerging diseases, epidemics, antimicrobial resistance, ...

Massive database maps links between brain development and mental health

A new large-scale, open data resource from the Perelman School of Medicine and collaborators helps researchers link brain ...
Frontiers

Showcasing FAIR² Data Articles: Unlocking Trustworthy, AI-Ready Scientific Data for Reuse and Impact

Scientific knowledge is fundamentally built on data; yet, for too long, research datasets have remained siloed, poorly ...
Frontiers

Interpretable machine learning models to predict survival in esophageal cancer: a study based on the SEER database and external validation in China

The final, formatted version of the article will be published soon. Objective:We developed interpretable machine learning(ML) models to predict the overall survival(OS) of esophageal cancer patients.