AIMC Topic: Diagnostic Errors
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[Clinical reasoning, the art of medicine and artificial intelligence].
Deutsche medizinische Wochenschrift (1946)
Nov 6, 2024
"Clinical reasoning" refers to all the thought processes that physicians use to make a diagnosis and determine a treatment and care plan. Artificial intelligence (AI) will enhance, improve, and accelerate human clinical diagnostic thinking, but it is...
Mitigating Diagnostic Errors in Lung Cancer Classification: A Multi-Eyes Principle to Uncertainty Quantification.
IEEE journal of biomedical and health informatics
Nov 6, 2024
In radiology, particularly in lung cancer diagnosis, diagnostic errors and cognitive biases pose substantial challenges. These issues, including perceptual errors, interpretive mistakes, and cognitive biases such as anchoring and premature closure, a...
Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study.
Journal of imaging informatics in medicine
Sep 11, 2024
We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired chest radiograph (CXR) and compare their performance with that of human experts. In this retrospective study, patient identification DL models were devel...
Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI): protocol for a prospective observational study.
BMJ open
Sep 5, 2024
INTRODUCTION: Missed fractures are the most frequent diagnostic error attributed to clinicians in UK emergency departments and a significant cause of patient morbidity. Recently, advances in computer vision have led to artificial intelligence (AI)-en...
Deep Learning for Distinguishing Mucinous Breast Carcinoma From Fibroadenoma on Ultrasound.
Clinical breast cancer
Sep 4, 2024
PURPOSE: Mucinous breast carcinoma (MBC) tends to be misdiagnosed as fibroadenomas (FA) due to its benign imaging characteristics. We aimed to develop a deep learning (DL) model to differentiate MBC and FA based on ultrasound (US) images. The model c...
Machine Learning to Enhance Electronic Detection of Diagnostic Errors.
JAMA network open
Sep 3, 2024
Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.
Journal of medical Internet research
Aug 26, 2024
BACKGROUND: Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay.
Assessing Laterality Errors in Radiology: Comparing Generative Artificial Intelligence and Natural Language Processing.
Journal of the American College of Radiology : JACR
Jul 1, 2024
PURPOSE: We compared the performance of generative artificial intelligence (AI) (Augmented Transformer Assisted Radiology Intelligence [ATARI, Microsoft Nuance, Microsoft Corporation, Redmond, Washington]) and natural language processing (NLP) tools ...
Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.
JMIR medical education
Jun 21, 2024
BACKGROUND: The persistence of diagnostic errors, despite advances in medical knowledge and diagnostics, highlights the importance of understanding atypical disease presentations and their contribution to mortality and morbidity. Artificial intellige...
Frequency and characteristics of errors by artificial intelligence (AI) in reading screening mammography: a systematic review.
Breast cancer research and treatment
Jun 9, 2024
PURPOSE: Artificial intelligence (AI) for reading breast screening mammograms could potentially replace (some) human-reading and improve screening effectiveness. This systematic review aims to identify and quantify the types of AI errors to better un...
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