AIMC Topic: Immunohistochemistry
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Annotation-Free Whole-Slide Image Analysis Method to Assess Immune Infiltration in Colorectal Cancer.
JCO precision oncology
May 7, 2025
PURPOSE: Tumor-infiltrating lymphocytes (TILs) play a crucial role in host antitumor processes. High level of TILs is associated with better outcomes for patients. We aim to automatically quantify TILs without any nuclei annotation and further constr...
Supervised Information Mining From Weakly Paired Images for Breast IHC Virtual Staining.
IEEE transactions on medical imaging
May 6, 2025
Immunohistochemistry (IHC) examination is essential to determine the tumour subtypes, provide key prognostic factors, and develop personalized treatment plans for breast cancer. However, compared to Hematoxylin and Eosin (H&E) staining, the preparati...
Machine learning prediction of HER2-low expression in breast cancers based on hematoxylin-eosin-stained slides.
Breast cancer research : BCR
Apr 18, 2025
BACKGROUND: Treatment with HER2-targeted therapies is recommended for HER2-positive breast cancer patients with HER2 gene amplification or protein overexpression. Interestingly, recent clinical trials of novel HER2-targeted therapies demonstrated pro...
Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer.
PeerJ
Apr 15, 2025
Programmed death-ligand 1 (PD-L1) is an important biomarker increasingly used as a predictive marker in breast cancer immunotherapy. Immunohistochemical quantification remains the standard method for assessment. However, it presents challenges relate...
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...
Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images.
European journal of cancer (Oxford, England : 1990)
Mar 26, 2025
BACKGROUND: Virtual staining is an artificial intelligence-based approach that transforms pathology images between stain types, such as hematoxylin and eosin (H&E) to immunohistochemistry (IHC), providing a tissue-preserving and efficient alternative...
Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.
Scientific reports
Mar 21, 2025
Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The immune system, particularly tertiary lymphoid structures (TLS), significantly influences CRC progression and prognosis. TLS maturation, especially in th...
TriDeNT : Triple deep network training for privileged knowledge distillation in histopathology.
Medical image analysis
Mar 18, 2025
Computational pathology models rarely utilise data that will not be available for inference. This means most models cannot learn from highly informative data such as additional immunohistochemical (IHC) stains and spatial transcriptomics. We present ...
Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection.
JCO clinical cancer informatics
Mar 4, 2025
PURPOSE: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratories use costly immunohistochemistry (IHC) for all cases to optimize workflow, often exceeding reimbur...
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