AIMC Topic: Ki-67 Antigen
Clear Filters Showing 1 to 10 of 63 articles
Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.
Scientific reports
Jul 29, 2025
The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessment is labor-intensive, requiring the counting of 500-2,000 cells in hotspots. Digital image analysis could streamline this process, yet few comprehensi...
Identification of proliferating neural progenitors in the adult human hippocampus.
Science (New York, N.Y.)
Jul 3, 2025
Continuous adult hippocampal neurogenesis is involved in memory formation and mood regulation but is challenging to study in humans. Difficulties finding proliferating progenitor cells called into question whether and how new neurons may be generated...
PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma.
Nuclear medicine communications
May 6, 2025
OBJECTIVE: PET image analysis provides tumor heterogeneity data related to neoadjuvant chemotherapy response (NACR) and metastatic risk in osteosarcoma. Ki-67 expression is used to predict metastasis. The accuracy of prediction models with image quan...
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...
Preoperative Assessment of Ki-67 Labeling Index in Pituitary Adenomas Using Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI.
Journal of magnetic resonance imaging : JMRI
Mar 17, 2025
BACKGROUND: Ki-67 labeling index (Ki-67 LI) is a proliferation marker that is correlated with aggressive behavior and prognosis of pituitary adenomas (PAs). Dynamic contrast-enhanced MRI (DCE-MRI) may potentially contribute to the preoperative assess...
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.
CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.
Abdominal radiology (New York)
Jan 22, 2025
BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31984
- Neural Networks, Computer 30211
- Algorithms 27388
- Deep Learning 26888
- Artificial Intelligence 24826
- Robotics 13382
- Image Processing, Computer-Assisted 9732
- Retrospective Studies 9334
- Magnetic Resonance Imaging 6342
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4864
- Support Vector Machine 4766
- Computational Biology 4331
- Brain 4126
- Computer Simulation 3932
Recent Journals
- Scientific reports 6743
- Sensors (Basel, Switzerland) 4794
- PloS one 4196
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1170
- Journal of chemical information and modeling 1064
- Nature communications 1039
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 860
- Briefings in bioinformatics 853