AIMC Topic: Ki-67 Antigen
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Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images.
PloS one
May 9, 2018
In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a trained pathologist using a manual method, which consists of counting e...
Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning.
PloS one
Apr 12, 2018
The World Health Organization (WHO) has clear guidelines regarding the use of Ki67 index in defining the proliferative rate and assigning grade for pancreatic neuroendocrine tumor (NET). WHO mandates the quantification of Ki67 index by counting at le...
An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.
Scientific reports
Jun 12, 2017
Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due t...
Investigation of serum Ki-67 as a biomarker in tumor-bearing dogs.
Research in veterinary science
Oct 26, 2016
Because of the limited number of tumor markers in veterinary medicine, there is need for identifying new markers. Ki-67 has been investigated as a tissue marker of malignant alterations. We hypothesized that Ki-67 would also be measurable in serum an...
Study on predicting breast cancer Ki-67 expression using a combination of radiomics and deep learning based on multiparametric MRI.
Magnetic resonance imaging
Sep 1, 2025
PURPOSE: To develop a multiparametric breast MRI radiomics and deep learning-based multimodal model for predicting preoperative Ki-67 expression status in breast cancer, with the potential to advance individualized treatment and precision medicine fo...
Diffusion Magnetic Resonance Imaging
Multiparametric Magnetic Resonance Imaging
Radiomics
Breast
Middle Aged
Humans
Image Processing, Computer-Assisted
Image Interpretation, Computer-Assisted
Female
Deep Learning
Aged
Contrast Media
Ki-67 Antigen
Reproducibility of Results
ROC Curve
Adult
Magnetic Resonance Imaging
Sensitivity and Specificity
Predictive Value of Tests
Breast Neoplasms
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...
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...
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...
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.
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...
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