Researchers at UMass Lowell have uncovered an innovative way to spot Alzheimer’s disease long before the first official diagnosis. By using machine learning to analyze clinical notes in electronic ...
A new proposal suggests using existing semantic HTML to mark sections of a page that are AI generated for EU regulatory ...
Abstract: Offline reinforcement learning (RL) learns policies from fixed-size datasets without interacting with the environment, while multi-agent reinforcement learning (MARL) faces challenges from ...
An estimated 60% of patients with Alzheimer's disease develop epilepsy or subclinical epileptiform activity over the course of the disease. New-onset seizures in cognitively healthy adults also ...
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
Abstract: In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in social ...
Nanosensors and Clean Energy Laboratory, Department of Chemistry & Nanoscience and Technology, PSG Institute of Advanced Studies, Coimbatore 641004, India Nanosensors and Clean Energy Laboratory, ...
ABSTRACT: Evaluating drug safety during pregnancy remains an ongoing clinical and pharmacological challenge due to ethical, practical, and regulatory barriers, resulting in scarce human clinical trial ...
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