AIMC Topic: Missed Diagnosis
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Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.
AJR. American journal of roentgenology
Jan 8, 2025
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...
Implementation of an AI Algorithm in Clinical Practice to Reduce Missed Incidental Pulmonary Embolisms on Chest CT and Its Impact on Short-Term Survival.
Investigative radiology
Oct 9, 2024
OBJECTIVES: A substantial number of incidental pulmonary embolisms (iPEs) in computed tomography scans are missed by radiologists in their daily routine. This study analyzes the radiological reports of iPE cases before and after implementation of an ...
Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?
World neurosurgery
May 16, 2024
BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, ...
Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).
Gastrointestinal endoscopy
Apr 16, 2024
BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5 mm adenomas and should undergo an early repeat colono...
Efficacy of artificial intelligence in reducing miss rates of GI adenomas, polyps, and sessile serrated lesions: a meta-analysis of randomized controlled trials.
Gastrointestinal endoscopy
Jan 4, 2024
BACKGROUND AND AIMS: The aim of this study was to determine if utilization of artificial intelligence (AI) in the course of endoscopic procedures can significantly diminish both the adenoma miss rate (AMR) and the polyp miss rate (PMR) compared with ...
Cross-Check QA: A Quality Assurance Workflow to Prevent Missed Diagnoses by Alerting Inadvertent Discordance Between the Radiologist and Artificial Intelligence in the Interpretation of High-Acuity CT Scans.
Journal of the American College of Radiology : JACR
Jul 8, 2023
PURPOSE: The aim of this study was to implement and evaluate a quality assurance (QA) workflow that leverages natural language processing to rapidly resolve inadvertent discordance between radiologists and an artificial intelligence (AI) decision sup...
Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Sep 14, 2021
BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously ...
Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.
Gastroenterology
Jun 17, 2020
BACKGROUND AND AIMS: Up to 30% of adenomas might be missed during screening colonoscopy-these could be polyps that appear on-screen but are not recognized by endoscopists or polyps that are in locations that do not appear on the screen at all. Comput...
Image Interpretation, Computer-Assisted
Adenomatous Polyps
Missed Diagnosis
Predictive Value of Tests
Male
Humans
Diagnosis, Computer-Assisted
Colonic Neoplasms
Reproducibility of Results
Middle Aged
Prospective Studies
Colonic Polyps
Deep Learning
Aged
Colonoscopy
Female
Young Adult
China
Adult
Adolescent
Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case series.
Medicine
Oct 23, 2020
RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it...
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