The accuracy of machine learning algorithms for predicting suicidal behavior is too low to be useful for screening or for ...

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

The accuracy of machine learning algorithms for predicting suicidal behavior is too low to be useful for screening or for prioritizing high-risk ...

An international team led by the Clínic-IDIBAPS-UB along with the Institute of Cancer Research, London, has developed a new ...

Snapchat is under fire from a Danish research body, Digitalt Ansvar, for allegedly allowing drug dealers to operate openly on its platform.

AI presents profound challenges to traditional competition regulation, with "algorithmic collusion" emerging as the most ...

Researcher Sophie Bell and professor Eric Turkheimer identified how genetics, environment and biology combine to affect ...

The study centers around a deep-learning tool named APEX, designed to predict antimicrobial activity from protein sequences.

A new imaging technique turns motion blur into an advantage, using a jiggling camera and a clever algorithm to create ...

Despite the growing adoption of XAI in CDSSs, the study points to significant usability and validation challenges that limit broader clinical integration. One of the most striking findings is that ...

Demographic bias gaps are closing in face recognition, but how training images are sourced is becoming the field’s biggest privacy fight.

A new study of Veterans Health Administration data shows that the Care Assessment Needs (CAN) algorithm — a tool used to predict whether veterans will be hospitalized or die in the 90 days after their ...