AIMC Topic: Pathologists
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Applications of Digital and Computational Pathology and Artificial Intelligence in Genitourinary Pathology Diagnostics.
Surgical pathology clinics
Dec 1, 2022
As machine learning (ML) solutions for genitourinary pathology image analysis are fostered by a progressively digitized laboratory landscape, these integrable modalities usher in a revolution in histopathological diagnosis. As technology advances, li...
Impact of artificial intelligence on pathologists' decisions: an experiment.
Journal of the American Medical Informatics Association : JAMIA
Sep 12, 2022
OBJECTIVE: The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this pape...
Artificial Intelligence in Kidney Cancer.
American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Apr 1, 2022
Artificial intelligence is rapidly expanding into nearly all facets of life, particularly within the field of medicine. The diagnosis, characterization, management, and treatment of kidney cancer is ripe with areas for improvement that may be met wit...
A Deep Learning Convolutional Neural Network Can Differentiate Between Helicobacter Pylori Gastritis and Autoimmune Gastritis With Results Comparable to Gastrointestinal Pathologists.
Archives of pathology & laboratory medicine
Jan 1, 2022
CONTEXT.—: Pathology studies using convolutional neural networks (CNNs) have focused on neoplasms, while studies in inflammatory pathology are rare. We previously demonstrated a CNN that differentiates reactive gastropathy, Helicobacter pylori gastri...
Introduction to Artificial Intelligence and Machine Learning for Pathology.
Archives of pathology & laboratory medicine
Oct 1, 2021
CONTEXT.—: Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and ou...
[A convolutional neural network based model for assisting pathological diagnoses on thyroid liquid-based cytology].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Apr 8, 2021
To develop a convolutional neural network based model for assisting pathological diagnoses on thyroid liquid-based cytology specimens. Seven-hundred thyroid TCT slides were collected, scanned for whole slide imaging (WSI), and divided into training...
Deep learning with transfer learning in pathology. Case study: classification of basal cell carcinoma.
Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Jan 1, 2021
Establishing basal cell carcinoma (BCC) subtype is sometimes challenging for pathologists. Deep-learning (DL) algorithms are an emerging approach in image classification due to their performance, accompanied by a new concept - transfer learning, whic...
An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.
The Lancet. Digital health
Aug 1, 2020
BACKGROUND: There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We report here on a blinded clinical vali...
Agreement of two pre-trained deep-learning neural networks built with transfer learning with six pathologists on 6000 patches of prostate cancer from Gleason2019 Challenge.
Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Jan 1, 2020
INTRODUCTION: While the visual inspection of histopathology images by expert pathologists remains the golden standard method for grading of prostate cancer the quest for developing automated algorithms for the job is set and deep-learning techniques ...
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