Whether estimating the probability that a disease is present or forecasting risk of deterioration,1 readmission,2 or death,3 most contemporary clinical artificial intelligence (AI) systems are ...
Abstract: Object state changes (OSCs) play a critical role in video understanding, as they focus on localizing the stages of state transitions within temporal sequences. However, existing methods face ...
This Clinical Nutrition opinion paper argues that nutrition research should stop asking whether a food is simply “healthy” ...
A new technical paper, “Causal AI For AMS Circuit Design: Interpretable Parameter Effects Analysis,” was published by the University of Florida. “Analog-mixed-signal (AMS) circuits are highly ...
Objective We employed a causal inference framework to estimate the counterfactual dose-response effects of light-intensity physical activity (LPA) on mortality across low, medium and high moderate- to ...
Nvidia CEO Jensen Huang debuted a new AI inference system during his GTC conference keynote. The product incorporates technology from Groq, with which Nvidia made a $20 billion deal. The chip can ...
In my day-to-day work, I have spent countless hours optimizing model performance, only to confront a sobering reality: In 2026, the primary barrier to widespread AI adoption has shifted. While raw ...
Abstract: Causal inference with spatial, temporal, and meta-analytic data commonly defaults to regression modeling. While widely accepted, such regression approaches can suffer from model ...
Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...
Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...
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