Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

Google DeepMind researchers have introduced ATLAS, a set of scaling laws for multilingual language models that formalize how model size, training data volume, and language mixtures interact as the ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...

Complex human diseases—such as cancer, neurodegenerative disorders, autoimmune conditions, cardiometabolic disease, and chronic inflammatory syndromes—arise ...

Abstract: Advancements in machine learning (ML) have facilitated the prediction of key aspects of human locomotion, particularly in identifying subject gait trajectories essential for recognizing ...

Background While the incidence of hospital adverse events appeared to be declining before 2019, the COVID-19 pandemic may ...

While experimentation is essential, traditional A/B testing can be excessively slow and expensive, according to DoorDash engineers Caixia Huang and Alex Weinstein. To address these limitations, they ...

This repository contains the official implementation for R3DM accepted at the International Conference on Machine Learning (ICML) 2025. It includes the source code for the ACORM and R3DM algorithms, ...

AI chatbots, including commercial market leaders such as ChatGPT, Google Gemini, and Claude, dispense advice that heavily ...

Triage, Critical Clinical Workflow Process, Chest Pain, Electrocardiogram (EKG), Door-to-EKG (DTE) Time Share and Cite: ...

Abstract: Remote sensing images exhibit multi-semantic char acteristics with abundant geographical and contextual information. Although multi-label learning methods demonstrate remark able advantages ...