UCSF researchers have discovered a way to identify deadly lung infections with improved accuracy by pairing AI with a unique ...

Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...

This repo contains the resources for the paper "From Accuracy to Robustness: A Study of Rule- and Model-based Verifiers in Mathematical Reasoning." In this work, we take mathematical reasoning as a ...

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Abstract: The increasing use of unmanned aerial vehicles (UAVs) highlights the need for robust classification systems. This study explores the impact of noise on UAV classification accuracy using ...

Abstract: The trust study was begun in the 1960s. Previous research has been particularly focused on understanding the psychological underpinnings of trust formation and sustenance, with influences ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...