Trained on historical consumption data spanning a decade, the model demonstrated strong predictive performance. It achieved a training error of 0.182 and a forecasting accuracy of 95.2 percent, ...

The study, titled “GenAI-Powered Framework for Reliable Sentiment Labeling in Drug Safety Monitoring,” published in Applied ...

Objectives To examine if early adoption into a family with favourable home environment conditions reduces long term ...

Objective Children and young people (CYP) with special educational needs (SENs) have an increased risk of psychopathology and ...

Background To investigate prevalence and risk factors of epiretinal membrane (ERM), particularly those associated with ERM ...

Background The high prevalence of atrial fibrillation (AF) and its association with cardiovascular (CV) outcomes represent a ...

EY's Joe Depa says he sees a split in staff. There's "high adoption, right out of the gate" for juniors but senior workers "are somewhat resistant." ...

This research introduces a VSLAM framework that optimizes obstacle avoidance in indoor logistics, leveraging advanced ...

Researchers conducted a systematic review to assess the risk of bias and applicability of prediction models for fear of recurrence in patients with cancer.

A locally trained sepsis model shows early warning potential in acute care, but its accuracy varies by the sepsis definition used, and high false positives limit its clinical utility.

Confidence is persuasive. In artificial intelligence systems, it is often misleading. Today's most capable reasoning models ...