ArticleJAMA dermatology2018
Population-Based Analysis of Histologically Confirmed Melanocytic Proliferations Using Natural Language Processing.
Article in JAMA dermatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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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.
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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.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.
- Natural language processing in dermatology: A systematic literature review and state of the art.Journal of the European Academy of Dermatology and Venereology : JEADV · 2024Pooled it
- In vivo molecular skin fluorescence imaging for noninvasive assessment of atypical nevi and melanoma: A validation trial.JAAD international · 2026Article
- Automated Detection of Benign and Malignant Skin Lesions from Reflectance Confocal Microscopy Images Using Deep Learning.JID innovations : skin science from molecules to population health · 2025Article
- Rapid diffused optical imaging for accurate 3D estimation of subcutaneous tissue features.iScience · 2025Article
- International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Article
- Mini review on skin biopsy: traditional and modern techniques.Frontiers in medicine · 2025Review
- Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4.Nature communications · 2024Article
- Recommended practices and ethical considerations for natural language processing-assisted observational research: A scoping review.Clinical and translational science · 2023Article
- Reproducibility of the histopathologic diagnosis of melanoma and related melanocytic lesions: Results from a testing study and a reference guide for providers.JAAD international · 2022Article
- Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing.JCO clinical cancer informatics · 2022Article
- Characterization of multiple diagnostic terms in melanocytic skin lesion pathology reports.Journal of cutaneous pathology · 2022Article
- Development and validation of an automated basal cell carcinoma histopathology information extraction system using natural language processing.Frontiers in surgery · 2022Article
- Automated analysis of whole slide digital skin biopsy images.Frontiers in artificial intelligence · 2022Article
- Terminology for melanocytic skin lesions and the MPATH-Dx classification schema: A survey of dermatopathologists.Journal of cutaneous pathology · 2021Article
- Scale-Aware Transformers for Diagnosing Melanocytic Lesions.IEEE access : practical innovations, open solutions · 2021Article
- Development and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials.JAMA network open · 2020Article
- Factors associated with use of immunohistochemical markers in the histopathological diagnosis of cutaneous melanocytic lesions.Journal of cutaneous pathology · 2020Article
- Application of natural language processing algorithms for extracting information from news articles in event-based surveillance.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2020Article
- Machine Learning in Dermatology: Current Applications, Opportunities, and Limitations.Dermatology and therapy · 2020Review
- Leveraging the electronic health record to improve dermatologic care delivery: The importance of finding structure in data.Journal of the American Academy of Dermatology · 2020Article
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Authors and funding
11 authors at 9 institutions in 2 countries.
Funding
Abstract
Importance: Population-based information on the distribution of histologic diagnoses associated with skin biopsies is unknown. Electronic medical records (EMRs) enable automated extraction of pathology report data to improve our epidemiologic understanding of skin biopsy outcomes, specifically those of melanocytic origin. Objective: To determine population-based frequencies and distribution of histologically confirmed melanocytic lesions. Design, Setting, and Participants: A natural language processing (NLP)-based analysis of EMR pathology reports of adult patients who underwent skin biopsies at a large integrated health care delivery system in the US Pacific Northwest from January 1, 2007, through December 31, 2012. Exposures: Skin biopsy procedure. Main Outcomes and Measures: The primary outcome was histopathologic diagnosis, obtained using an NLP-based system to process EMR pathology reports. We determined the percentage of diagnoses classified as melanocytic vs nonmelanocytic lesions. Diagnoses classified as melanocytic were further subclassified using the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) reporting schema into the following categories: class I (nevi and other benign proliferations such as mildly dysplastic lesions typically requiring no further treatment), class II (moderately dysplastic and other low-risk lesions that may merit narrow reexcision with <5-mm margins), class III (eg, melanoma in situ and other higher-risk lesions warranting reexcision with 5-mm to 1-cm margins), and class IV/V (invasive melanoma requiring wide reexcision with ≥1-cm margins and potential adjunctive therapy). Health system cancer registry data were used to define the percentage of invasive melanoma cases within MPATH-Dx class IV (stage T1a) vs V (≥stage T1b). Results: A total of 80 368 skin biopsies, performed on 47 529 patients, were examined. Nearly 1 in 4 skin biopsies were of melanocytic lesions (23%; n = 18 715), which were distributed according to MPATH-Dx categories as follows: class I, 83.1% (n = 15 558); class II, 8.3% (n = 1548); class III, 4.5% (n = 842); class IV, 2.2% (n = 405); and class V, 1.9% (n = 362). Conclusions and Relevance: Approximately one-quarter of skin biopsies resulted in diagnoses of melanocytic proliferations. These data provide the first population-based estimates across the spectrum of melanocytic lesions ranging from benign through dysplastic to malignant. These results may serve as a foundation for future research seeking to understand the epidemiology of melanocytic proliferations and optimization of skin biopsy utilization.
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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.