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

In asset-intensive industries, misclassified parts and inaccurate bills of materials cost far more than storeroom space. AI ...

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

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

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 ...

Today’s AI is still unreliable. Some researchers think solving that problem requires teaching AI systems to understand the world around them.

In practice, retrieval is a system with its own failure modes, its own latency budget and its own quality requirements.

This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...

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