AIMC Topic: Diagnostic Errors
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From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.
Clinical chemistry and laboratory medicine
Jan 28, 2025
This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence...
Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.
JMIR formative research
Jan 22, 2025
BACKGROUND: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions ...
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 ...
Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.
BMJ open gastroenterology
Jan 6, 2025
OBJECTIVE: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an A...
Faster and better than a physician?: Assessing diagnostic proficiency of ChatGPT in misdiagnosed individuals with neuromyelitis optica spectrum disorder.
Journal of the neurological sciences
Dec 19, 2024
BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a commonly misdiagnosed condition. Driven by cost-consciousness and technological fluency, distinct generations may gravitate towards healthcare alternatives, including artificial intellig...
Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Dec 15, 2024
Diagnostic errors in health care pose significant risks to patient safety and are disturbingly common. In the emergency department (ED), the chaotic and high-pressure environment increases the likelihood of these errors, as emergency clinicians must ...
Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay.
Current problems in diagnostic radiology
Dec 10, 2024
In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms ar...
Facilitating Trust Calibration in Artificial Intelligence-Driven Diagnostic Decision Support Systems for Determining Physicians' Diagnostic Accuracy: Quasi-Experimental Study.
JMIR formative research
Nov 27, 2024
BACKGROUND: Diagnostic errors are significant problems in medical care. Despite the usefulness of artificial intelligence (AI)-based diagnostic decision support systems, the overreliance of physicians on AI-generated diagnoses may lead to diagnostic ...
Generating synthetic clinical text with local large language models to identify misdiagnosed limb fractures in radiology reports.
Artificial intelligence in medicine
Nov 20, 2024
Large language models (LLMs) demonstrate impressive capabilities in generating human-like content and have much potential to improve the performance and efficiency of healthcare. An important application of LLMs is to generate synthetic clinical repo...
Bias Sensitivity in Diagnostic Decision-Making: Comparing ChatGPT with Residents.
Journal of general internal medicine
Nov 7, 2024
BACKGROUND: Diagnostic errors, often due to biases in clinical reasoning, significantly affect patient care. While artificial intelligence chatbots like ChatGPT could help mitigate such biases, their potential susceptibility to biases is unknown.
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