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

The Gulf Coast is recognized worldwide for its exceptional fishing opportunities, offering anglers a wide variety of species ...

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...

Dr. Alan Kuhnle, assistant professor in the computer science and engineering department at Texas A&M University, is using smartphone mobility data collected from anglers to develop machine-learning ...

Kumo, a leader in predictive AI, today announced its launch of KumoRFM-2, the first foundation model to outperform fully supervised machine learning on enterprise relational data. Built by the team ...

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...

An intelligent monitoring pipe combines optical sensing with machine learning algorithms to monitor and predict 3D soil settlement, which could help provide early warnings of risks from soil ...

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...

Bipolar disorder is a complex psychiatric condition characterized by alternating mood episodes, ranging from depression to mania. Accurate and timely detection of a patient’s current mood state is ...

Abstract: This study evaluates the performance of eight machine learning models such as Gradient Boosting, Logistic Regression, Naïve Bayes, Linear Discriminant Analysis (LDA), Random Forest, Support ...