AIMC Topic: Ki-67 Antigen

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Multi-task learning for joint prediction of breast cancer histological indicators in dynamic contrast-enhanced magnetic resonance imaging.

Computer methods and programs in biomedicine Jul 1, 2025
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...
Machine Learning Algorithms Prognosis Humans Contrast Media Magnetic Resonance Imaging Ki-67 Antigen Female Breast Neoplasms Deep Learning
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Artificial intelligence-powered optimization of KI-67 assessment in breast cancer: enhancing precision and workflow efficiency. a literature review.

JPMA. The Journal of the Pakistan Medical Association Apr 1, 2024
Breast Cancer (BC) has evolved from traditional morphological analysis to molecular profiling, identifying new subtypes. Ki-67, a prognostic biomarker, helps classify subtypes and guide chemotherapy decisions. This review explores how artificial inte...
Artificial Intelligence Female Breast Neoplasms Humans Ki-67 Antigen Biomarkers, Tumor Workflow
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Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

Cancer medicine Apr 1, 2024
OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pa...
Eosine Yellowish-(YS) Algorithms Biomarkers, Tumor Humans Nomograms Retrospective Studies Artificial Intelligence Ki-67 Antigen Colorectal Neoplasms
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Radiomic Machine Learning in Invasive Ductal Breast Cancer: Prediction of Ki-67 Expression Level Based on Radiomics of DCE-MRI.

Technology in cancer research & treatment Jan 1, 2024
PURPOSE: Our study aimed to investigate the potential of radiomics with DCE-MRI for predicting Ki-67 expression in invasive ductal breast cancer.
Ki-67 Antigen Middle Aged Breast Neoplasms ROC Curve Humans Prognosis Magnetic Resonance Imaging Radiomics Machine Learning Area Under Curve Retrospective Studies Aged Biomarkers, Tumor Image Interpretation, Computer-Assisted Female Adult Carcinoma, Ductal, Breast
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An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in TNM Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study.

Technology in cancer research & treatment Jan 1, 2024
To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-associated nuclear antigen Ki-67 value ≥ 15% in TNM stage primary breast cancer (BC). Data were coll...
ROC Curve Neoadjuvant Therapy Follow-Up Studies Middle Aged Ultrasonography Neoplasm Staging Ki-67 Antigen Aged Adult Breast Neoplasms Radiomics Biomarkers, Tumor Machine Learning Prognosis Female Humans
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Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Mar 1, 2023
Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. Nonetheless, and perhaps surprisingly, only few image AI systems ...
Ki-67 Antigen Estrogens Receptors, Estrogen Humans Receptors, Progesterone Artificial Intelligence Female Reproducibility of Results Breast Neoplasms
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Deep-Learning-Based Evaluation of Dual Stain Cytology for Cervical Cancer Screening: A New Paradigm.

Journal of the National Cancer Institute Nov 2, 2021
Mass Screening Humans Early Detection of Cancer Female Coloring Agents Vaginal Smears Cytodiagnosis Uterine Cervical Neoplasms Ki-67 Antigen Papillomavirus Infections Deep Learning Papillomaviridae
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Deep Learning Model based Ki-67 Index estimation with Automatically Labelled Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Ki-67 labelling index is a biomarker which is used across the world to predict the aggressiveness of cancer. To compute the Ki-67 index, pathologists normally count the tumour nuclei from the slide images manually; hence it is timeconsuming and is su...
Ki-67 Antigen Machine Learning Humans Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted
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