Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

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

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

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

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 ...

A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...