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 ...

n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...

Retrospective validation of a novel multimodal AI prognostic tool integrating digital pathology and clinical data against real world data and Oncotype DX in a Swiss breast cancer cohort. This is an ...

Local factors such as seasonal temperature, the year-dependent water and vegetation index, and data on animal density can be used to predict regional outbreaks of avian flu in Europe. This is the ...

Researchers develop radiomics-based predictive models to assess the likelihood of progressively refractory intracranial hypertension leading to secondary DC. The multiomic model, which incorporated ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A new artificial intelligence tool could aid in limiting or even prevent pandemics by identifying animal species that may harbor and spread viruses capable of infecting humans. The machine learning ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

A new machine learning approach developed through an international collaboration between Polytechnic University of Milan and Drexel University could help architects and urban planners better predict ...