AIMC Topic: Immunohistochemistry
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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...
[Artificial intelligence: a solution for the lack of pathologists?].
Der Pathologe
Apr 11, 2022
Given the rapid developments, there is no doubt that artificial intelligence (AI) will substantially impact pathological diagnostics. However, it remains an open question if AI will primarily be another diagnostic tool, such as immunohistochemistry, ...
Deep learning based on hematoxylin-eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma.
The Journal of pathology
Mar 31, 2022
In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond to chemotherapy or immunotherapy, according to the TCGA. In clinical practice, however, not every patient undergoes molecular testing. Many laboratorie...
Objective quantification of nerves in immunohistochemistry specimens of thyroid cancer utilising deep learning.
PLoS computational biology
Feb 28, 2022
Accurate quantification of nerves in cancer specimens is important to understand cancer behaviour. Typically, nerves are manually detected and counted in digitised images of thin tissue sections from excised tumours using immunohistochemistry. Howeve...
Quantitative Assessment of Epithelial Proliferation in Rat Mammary Gland Using Artificial Intelligence Independent of Choice of Proliferation Marker.
The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society
Jan 20, 2022
Epithelial proliferation in the rat mammary gland is recommended in regulatory guidelines as an endpoint for assessment of the in vivo carcinogenic potential of insulin analogues. Epithelial proliferation is traditionally assessed by immunohistochemi...
Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry.
Pathobiology : journal of immunopathology, molecular and cellular biology
Dec 30, 2021
Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades. Examples include automated tissue processing and staining, digital data processing, storing and management, voice recognition sys...
Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry.
Biomolecules
Dec 23, 2021
Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue sections. However, it suffers from several disadvantages, including its lack of objectivity and the ...
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