To our knowledge, this analysis is the largest EHR-based study for identifying drug repurposing candidates for ALS. We identified several drugs that warrant further assessment as therapeutic options ...

For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...

Abstract: Phishing attacks remain a critical threat in the digital era, exploiting social engineering tactics to compromise user trust and sensitive information, often resulting in financial loss and ...

aShanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information ...

This project implements a fully autonomous multi-agent system that diagnoses Facebook Ads performance issues, identifies causes of ROAS decline, and generates data-driven creative recommendations. It ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

The integration of soft computing and machine learning into healthcare systems is increasing due to their effectiveness and precision (Javaid et al., 2022; Abdelaziz et al., 2018). In recent years, ...

Cooper King climbed into the machine at Soccer Dome in Webster Groves, Missouri, on Saturday, Feb. 7 Latoya Gayle joined PEOPLE as an Associate Editor in 2024. Her work has previously appeared in The ...

Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...