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.

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

The ADB–Cornell study finds that machine learning poverty maps often misfire, overestimating welfare in poor, rural, ...

Abstract: With the rapid development of computer vision technology, image recognition, as one of its core tasks, plays an important role in several industries. However, traditional image recognition ...

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 ...

Abstract: Smart algorithms have significant advantages in many fields, especially in the application of ultrasonic sensing technology. First, smart algorithms can effectively process and analyze large ...

Background: Shift work is increasingly common and associated with numerous adverse health effects. Although studies show that shift work affects brain structure and neurological stress, its direct ...