Search Results for author:
Found 4 papers, 0 papers with code
Real-World Performance of Autonomously Reporting Normal Chest Radiographs in NHS Trusts Using a Deep-Learning Algorithm on the GP Pathway
AIM To analyse the performance of a deep-learning (DL) algorithm currently deployed as diagnostic decision support software in two NHS Trusts used to identify normal chest x-rays in active clinical pathways.
Enhancing Early Lung Cancer Detection on Chest Radiographs with AI-assistance: A Multi-Reader Study
Design: This retrospective study evaluated the performance of 11 clinicians for detecting lung cancer from chest radiographs, with and without assistance from a commercially available AI algorithm (red dot, Behold. ai) that predicts suspected lung cancer from CXRs.
Robustness of an Artificial Intelligence Solution for Diagnosis of Normal Chest X-Rays
This study evaluates the robustness of an AI solution for the diagnosis of normal chest X-rays (CXRs) by comparing performance across multiple patient and environmental subgroups, as well as comparing AI errors with those made by human experts.
Modeling Discourse Segments in Lyrics Using Repeated Patterns
This study proposes a computational model of the discourse segments in lyrics to understand and to model the structure of lyrics.
