AIMC Topic: Ki-67 Antigen
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Exploring the potential of machine learning in gastric cancer: prognostic biomarkers, subtyping, and stratification.
BMC cancer
Apr 30, 2025
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most impo...
Digital quantification of Ki67 and PRAME in challenging melanocytic lesions - A novel diagnostic tool.
Pathology, research and practice
Mar 31, 2025
The interpretation of immunohistochemical markers in melanocytic lesions possesses difficulties due to expression in non-melanocytic cells and the time-consuming, non-reproducible nature of manual assessment. A digital tool that accurately quantifies...
Toward Accurate Deep Learning-Based Prediction of Ki67, ER, PR, and HER2 Status From H&E-Stained Breast Cancer Images.
Applied immunohistochemistry & molecular morphology : AIMM
Mar 27, 2025
Despite improvements in machine learning algorithms applied to digital pathology, only moderate accuracy, to predict molecular information from histology alone, has been achieved so far. One of the obstacles is the lack of large data sets to properly...
Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.
Scientific reports
Mar 25, 2025
Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machine learning model that accurately predicts Ki-67 expression level. This multi-center retrospective study analyzed clinical and ultrasound data from 92...
DCE-MRI based deep learning analysis of intratumoral subregion for predicting Ki-67 expression level in breast cancer.
Magnetic resonance imaging
Mar 13, 2025
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.
Academic radiology
Jan 9, 2025
RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machine learning (ML) models for preoperative Ki-67 expression prediction in clear cell renal cell carcinoma (ccRCC).
The value of multiparametric MRI radiomics and machine learning in predicting preoperative Ki-67 expression level in breast cancer.
BMC medical imaging
Jan 7, 2025
OBJECTIVE: This study was to develop a multi-parametric MRI radiomics model to predict preoperative Ki-67 status.
Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.
BMC cancer
Dec 11, 2024
BACKGROUND: In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 pr...
Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.
Scientific reports
Nov 26, 2024
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...
Application of Artificial Intelligence in Prediction of Ki-67 Index in Meningiomas: A Systematic Review and Meta-Analysis.
World neurosurgery
Nov 18, 2024
BACKGROUND: The Ki-67 index is a histopathological marker that has been reported to be a crucial factor in the biological behavior and prognosis of meningiomas. Several studies have developed artificial intelligence (AI) models to predict the Ki-67 b...
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