AIMC Topic: Ki-67 Antigen

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Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study.

Clinical neurology and neurosurgery May 17, 2022
OBJECTIVES: Ki67 is an important biomarker of pituitary adenoma (PA) aggressiveness. In this study, PA invasion of surrounding structures is investigated and deep learning (DL) models are established for preoperative prediction of Ki67 labeling index...
Magnetic Resonance Imaging Humans Pituitary Neoplasms Retrospective Studies Adenoma Deep Learning Ki-67 Antigen
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Compound computer vision workflow for efficient and automated immunohistochemical analysis of whole slide images.

Journal of clinical pathology Feb 15, 2022
AIMS: Immunohistochemistry (IHC) assessment of tissue is a central component of the modern pathology workflow, but quantification is challenged by subjective estimates by pathologists or manual steps in semi-automated digital tools. This study integr...
Computers Brain Neoplasms Image Processing, Computer-Assisted Workflow Humans Neural Networks, Computer Ki-67 Antigen
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Artificial intelligence-assisted interpretation of Ki-67 expression and repeatability in breast cancer.

Diagnostic pathology Jan 30, 2022
BACKGROUND: Ki-67 standard reference card (SRC) and artificial intelligence (AI) software were used to evaluate breast cancer Ki-67LI. We established training and validation sets and studied the repeatability inter-observers.
Artificial Intelligence Female Reproducibility of Results Breast Neoplasms Humans Observer Variation Ki-67 Antigen
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Quantitative Assessment of Epithelial Proliferation in Rat Mammary Gland Using Artificial Intelligence Independent of Choice of Proliferation Marker.

The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society Jan 20, 2022
Epithelial proliferation in the rat mammary gland is recommended in regulatory guidelines as an endpoint for assessment of the in vivo carcinogenic potential of insulin analogues. Epithelial proliferation is traditionally assessed by immunohistochemi...
Ki-67 Antigen Cell Proliferation Rats, Sprague-Dawley Biomarkers Bromodeoxyuridine Female Epithelium Animals Artificial Intelligence Immunohistochemistry Rats Mammary Glands, Animal Histones
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Artificial image objects for classification of breast cancer biomarkers with transcriptome sequencing data and convolutional neural network algorithms.

Breast cancer research : BCR Oct 10, 2021
BACKGROUND: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expressio...
Biomarkers, Tumor Transcriptome Databases, Genetic Survival Analysis Female Reproducibility of Results Breast Neoplasms Image Interpretation, Computer-Assisted Ki-67 Antigen Humans Neural Networks, Computer Algorithms
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Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

Histopathology Jun 24, 2021
AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article w...
Image Interpretation, Computer-Assisted Observer Variation Ki-67 Antigen Pathology, Clinical Reproducibility of Results Artificial Intelligence Breast Neoplasms Retrospective Studies Biomarkers, Tumor Female Humans Microscopy
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The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice.

Histopathology May 30, 2021
AIMS: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and...
Humans Artificial Intelligence Research Design Data Accuracy Biomarkers, Tumor Observer Variation Diagnosis, Computer-Assisted Immunohistochemistry Image Processing, Computer-Assisted Calibration Pathologists Ki-67 Antigen Retrospective Studies Pathology, Clinical Reproducibility of Results Breast Neoplasms
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PathoNet introduced as a deep neural network backend for evaluation of Ki-67 and tumor-infiltrating lymphocytes in breast cancer.

Scientific reports Apr 19, 2021
The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as prognostic factors in predicting both tumor progression and probable response to chemotherapy. The value of Ki-67 index and TILs in approach to heterogeneous ...
Biomarkers, Tumor Middle Aged Lymphocytes, Tumor-Infiltrating Ki-67 Antigen Prognosis Humans Female Neural Networks, Computer Adult Breast Neoplasms
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Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning.

Scientific reports Jul 6, 2020
The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the ...
Ki-67 Antigen Humans Reproducibility of Results Observer Variation Deep Learning Immunohistochemistry Neoplasm Grading Synaptophysin Gastrointestinal Neoplasms Neuroendocrine Tumors
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Hypothesis-free deep survival learning applied to the tumour microenvironment in gastric cancer.

The journal of pathology. Clinical research Jun 27, 2020
The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we p...
Antigens, Differentiation, Myelomonocytic CD8 Antigens Antigens, CD20 Ki-67 Antigen Time Factors Tumor Microenvironment Tissue Array Analysis Cell Proliferation Biomarkers, Tumor Predictive Value of Tests Antigens, CD Humans Risk Assessment Risk Factors Deep Learning Neoplasm Staging Stomach Neoplasms Image Interpretation, Computer-Assisted Immunohistochemistry
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