Introduction People identified as higher risk by a machine learning algorithm (Future Innovations in Novel Detection of Atrial Fibrillation [FIND-AF]) are at increased risk of ...

Purpose: The purpose of this study was to evaluate the effectiveness of implementation of an FDA-cleared artificial intelligence (AI) solution (Aidoc, Tel Aviv, Israel) for detecting intracranial ...

Yet, algorithms to support intervention during patient encounters are lacking, with accurate LTOT identification in routine care being the essential first step. Objective: This study aims to develop ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

Background Rapid triage of patients presenting with chest pain is essential for early diagnosis and safe disposition. The European Society of Cardiology (ESC) 0/1-hour hs-cTn algorithm has shown ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Clathrate hydrates are crystalline inclusion compounds with relevance to global ...

Proposal: Add a dedicated clusterName value (like there is in the robusta helm chart) that automatically sets the CLUSTER_NAME env var: ...

Automated detection of metallophore biosynthesis reveals that metal-chelating non-ribosomal peptides are widespread, chemically diverse, and deeply rooted in bacterial evolution.

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...

Low back pain (LBP), primarily driven by intervertebral disc degeneration (IDD), imposes a significant global health burden. While type 2 diabetes mellitus (T2DM) is a recognized risk factor for IDD, ...