AIMC Topic: Diagnostic Errors
Clear Filters Showing 21 to 30 of 99 articles
Explanatory argumentation in natural language for correct and incorrect medical diagnoses.
Journal of biomedical semantics
May 30, 2024
BACKGROUND: A huge amount of research is carried out nowadays in Artificial Intelligence to propose automated ways to analyse medical data with the aim to support doctors in delivering medical diagnoses. However, a main issue of these approaches is t...
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, ...
AI in radiology: Legal responsibilities and the car paradox.
European journal of radiology
Apr 10, 2024
The integration of AI in radiology raises significant legal questions about responsibility for errors. Radiologists fear AI may introduce new legal challenges, despite its potential to enhance diagnostic accuracy. AI tools, even those approved by reg...
The Promise of Reciprocal Human and Machine Learning for Observational Error Reduction in Diagnostic Imaging.
Academic radiology
Apr 4, 2024
Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation.
European radiology
Mar 11, 2024
OBJECTIVES: To evaluate an artificial intelligence (AI)-assisted double reading system for detecting clinically relevant missed findings on routinely reported chest radiographs.
Toward the eradication of medical diagnostic errors.
Science (New York, N.Y.)
Jan 25, 2024
The medical community does not broadcast the problem, but there are many studies that have reinforced a serious issue with diagnostic errors. A recent study concluded: "We estimate that nearly 800,000 Americans die or are permanently disabled by diag...
Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study.
Journal of medical Internet research
Jan 22, 2024
BACKGROUND: Benefiting from rich knowledge and the exceptional ability to understand text, large language models like ChatGPT have shown great potential in English clinical environments. However, the performance of ChatGPT in non-English clinical set...
Machine learning-based delta check method for detecting misidentification errors in tumor marker tests.
Clinical chemistry and laboratory medicine
Dec 14, 2023
OBJECTIVES: Misidentification errors in tumor marker tests can lead to serious diagnostic and treatment errors. This study aims to develop a method for detecting these errors using a machine learning (ML)-based delta check approach, overcoming limita...
Enhancing human-AI collaboration: The case of colonoscopy.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Nov 6, 2023
Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows promise in mitigating this burden by supporting Medical Doctors in decision-making. However, the mere display of excellent or even superhuman performance...
The uncovered biases and errors in clinical determination of bone age by using deep learning models.
European radiology
Dec 20, 2022
OBJECTIVES: To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA.
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