ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2023
From Image to Diagnosis: Characterizing Sources of Error in Histopathologic Interpretation.
Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Interobserver Variability Across Whole-Slide Imaging Systems.Archives of pathology & laboratory medicine · 2026Article
- Artificial intelligence and computer-aided diagnosis in diagnostic decisions: 5 questions for medical informatics and human-computer interface research.Journal of the American Medical Informatics Association : JAMIA · 2026Review
- Characterizing Interpretive and Diagnostic Competency Development in Pathology Training.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Article
- Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.Scientific reports · 2025Article
- Assessing the diagnostic accuracy of ChatGPT-4 in the histopathological evaluation of liver fibrosis in MASH.Hepatology communications · 2025Article
- Robust ROI Detection in Whole Slide Images Guided by Pathologists' Viewing Patterns.Journal of imaging informatics in medicine · 2025Article
- Eye tracking in digital pathology: A comprehensive literature review.Journal of pathology informatics · 2024Review
- Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Medicinal polypharmacology-a scientific glossary of terminology and concepts.Frontiers in pharmacology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
An accurate histopathologic diagnosis on surgical biopsy material is necessary for the clinical management of patients and has important implications for research, clinical trial design/enrollment, and public health education. This study used a mixed methods approach to isolate sources of diagnostic error while residents and attending pathologists interpreted digitized breast biopsy slides. Ninety participants, including pathology residents and attending physicians at major United States medical centers reviewed a set of 14 digitized whole-slide images of breast biopsies. Each case had a consensus-defined diagnosis and critical region of interest (cROI) representing the most significant pathology on the slide. Participants were asked to view unmarked digitized slides, draw their participant region of interest (pROI), describe its features, and render a diagnosis. Participants' review behavior was tracked using case viewer software and an eye-tracking device. Diagnostic accuracy was calculated in comparison to the consensus diagnosis. We measured the frequency of errors emerging during 4 interpretive phases: (1) detecting the cROI, (2) recognizing its relevance, (3) using the correct terminology to describe findings in the pROI, and (4) making a diagnostic decision. According to eye-tracking data, trainees and attending pathologists were very likely (∼94% of the time) to find the cROI when inspecting a slide. However, trainees were less likely to consider the cROI relevant to their diagnosis. Pathology trainees (41% of cases) were more likely to use incorrect terminology to describe pROI features than attending pathologists (21% of cases). Failure to accurately describe features was the only factor strongly associated with an incorrect diagnosis. Identifying where errors emerge in the interpretive and/or descriptive process and working on building organ-specific feature recognition and verbal fluency in describing those features are critical steps for achieving competency in diagnostic decision making.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.