AIMC Topic: Pathologists
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Pathologist-level classification of histopathological melanoma images with deep neural networks.
European journal of cancer (Oxford, England : 1990)
May 23, 2019
BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high discordance between individual pathologists. For melanoma, the literature reports 25-26% ...
Cancer taxonomy: pathology beyond pathology.
European journal of cancer (Oxford, England : 1990)
May 17, 2019
The way we categorise and classify cancer types dictates not only the way we diagnose and treat patients but also many of our decisions on biomarker and drug development. In addition, cancer taxonomy proves the ground truth for future discoveries in ...
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks.
Scientific reports
Mar 4, 2019
Classification of histologic patterns in lung adenocarcinoma is critical for determining tumor grade and treatment for patients. However, this task is often challenging due to the heterogeneous nature of lung adenocarcinoma and the subjective criteri...
Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists.
Archives of pathology & laboratory medicine
Oct 8, 2018
CONTEXT.—: Nodal metastasis of a primary tumor influences therapy decisions for a variety of cancers. Histologic identification of tumor cells in lymph nodes can be laborious and error-prone, especially for small tumor foci.
Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.
Journal of hepatology
May 1, 2025
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...
General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.
Archives of pathology & laboratory medicine
Apr 1, 2025
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based model...
A survey analysis of the adoption of large language models among pathologists.
American journal of clinical pathology
Jan 28, 2025
OBJECTIVES: We sought to investigate the adoption and perception of large language model (LLM) applications among pathologists.
Thinking like a pathologist: Morphologic approach to hepatobiliary tumors by ChatGPT.
American journal of clinical pathology
Jan 28, 2025
OBJECTIVES: This research aimed to evaluate the effectiveness of ChatGPT in accurately diagnosing hepatobiliary tumors using histopathologic images.
Artificial intelligence-enabled histology exhibits comparable accuracy to pathologists in assessing histological remission in ulcerative colitis: a systematic review, meta-analysis, and meta-regression.
Journal of Crohn's & colitis
Jan 11, 2025
BACKGROUND AND AIMS: Achieving histological remission is a desirable emerging treatment target in ulcerative colitis (UC), yet its assessment is challenging due to high inter- and intraobserver variability, reliance on experts, and lack of standardiz...
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