AIMC Topic: Immunohistochemistry
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Novel B-DNA dermatophyte assay for demonstration of canonical DNA in dermatophytes: Histopathologic characterization by artificial intelligence.
Clinics in dermatology
Jan 6, 2024
We describe a novel assay and artificial intelligence-driven histopathologic approach identifying dermatophytes in human skin tissue sections (ie, B-DNA dermatophyte assay) and demonstrate, for the first time, the presence of dermatophytes in tissue ...
Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Dec 1, 2023
Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB),...
Combined colour deconvolution and artificial intelligence approach for region-selective immunohistochemical labelling quantification: The example of alpha smooth muscle actin in mouse kidney.
Journal of biophotonics
Nov 7, 2023
Immunohistochemical (IHC) localisation of protein expression is a widely used tool in pathology. This is semi-quantitative and exhibits substantial intra- and inter-observer variability. Digital approaches based on stain quantification applied to IHC...
Automating Ground Truth Annotations for Gland Segmentation Through Immunohistochemistry.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Sep 15, 2023
Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of inflammatory bowel disease and cancer. When properly trained, deep learning pipelines can provide a systematic, reproducible, and quantitative assessment of dis...
Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jun 19, 2023
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial int...
Automated Ki-67 labeling index assessment in prostate cancer using artificial intelligence and multiplex fluorescence immunohistochemistry.
The Journal of pathology
Mar 6, 2023
The Ki-67 labeling index (Ki-67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification of Ki-67 immunostaining in 200-500 tumor cells. To enable automated Ki-67 LI assessment in routine c...
Automated Molecular Subtyping of Breast Carcinoma Using Deep Learning Techniques.
IEEE journal of translational engineering in health and medicine
Feb 6, 2023
OBJECTIVE: Molecular subtyping is an important procedure for prognosis and targeted therapy of breast carcinoma, the most common type of malignancy affecting women. Immunohistochemistry (IHC) analysis is the widely accepted method for molecular subty...
An open source pipeline for quantitative immunohistochemistry image analysis of inflammatory skin disease using artificial intelligence.
Journal of the European Academy of Dermatology and Venereology : JEADV
Dec 3, 2022
BACKGROUND: The application of artificial intelligence (AI) to whole slide images has the potential to improve research reliability and ultimately diagnostic efficiency and service capacity. Image annotation plays a key role in AI and digital patholo...
Development of an automated combined positive score prediction pipeline using artificial intelligence on multiplexed immunofluorescence images.
Computers in biology and medicine
Nov 24, 2022
Immunotherapy targeting immune checkpoint proteins, such as programmed cell death ligand 1 (PD-L1), has shown impressive outcomes in many clinical trials but only 20%-40% of patients benefit from it. Utilizing Combined Positive Score (CPS) to evaluat...
Using Deep Learning to Predict Final HER2 Status in Invasive Breast Cancers That are Equivocal (2+) by Immunohistochemistry.
Applied immunohistochemistry & molecular morphology : AIMM
Oct 17, 2022
Invasive breast carcinomas are routinely tested for HER2 using immunohistochemistry (IHC), with reflex in situ hybridization (ISH) for those scored as equivocal (2+). ISH testing is expensive, time-consuming, and not universally available. In this st...
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