A recent study shows that 1 in 5 people use AI every day. From the chatbot helping you budget smarter to the recommendations ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

Time-to-event is a powerful statistical approach increasingly used in sports science and medicine to examine time-to-event outcomes such as time to sports injury occurrence, career duration and ...

The performance of skilled behaviors requires a balance between consistency and adaptability. Although the neural mechanisms that regulate this balance have been extensively studied at systems and ...

SignalHire, a leading provider in the contact intelligence space, has achieved a 96% accuracy rate through advanced machine learning algorithms and real-time verification systems. The platform ...

In a data-driven world, the ability to analyze and interpret information is critical. Harvard University’s Professional ...

This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...

By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...

A research team of mathematicians and computer scientists has used machine learning to reveal new mathematical structure within the theory of finite groups. By training neural networks to recognise ...

A go-to software platform scientists use to do their work could become less glitchy, thanks to University of Alberta research.

Objective: This study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney ...

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...