AIMC Topic: Immunohistochemistry
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Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.
British journal of cancer
Jul 21, 2020
BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the current study, we aimed to predict the genetic information of pancreatic tumours in a simple, inexpensive, and non-invasive manner, using cancer imaging...
Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning.
Scientific reports
Jul 6, 2020
The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the ...
Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.
The Journal of pathology
Jul 1, 2020
Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background in over one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and several other tumours. Mutation...
Hypothesis-free deep survival learning applied to the tumour microenvironment in gastric cancer.
The journal of pathology. Clinical research
Jun 27, 2020
The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we p...
Antigens, Differentiation, Myelomonocytic
CD8 Antigens
Cell Proliferation
Predictive Value of Tests
Antigens, CD
Neoplasm Staging
Image Interpretation, Computer-Assisted
Tumor Microenvironment
Immunohistochemistry
Humans
Biomarkers, Tumor
Antigens, CD20
Risk Factors
Risk Assessment
Ki-67 Antigen
Stomach Neoplasms
Deep Learning
Tissue Array Analysis
Time Factors
Deep Learning Identifies Cardiomyocyte Nuclei With High Precision.
Circulation research
Jun 3, 2020
Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation.
Scientific reports
May 5, 2020
Restoration of the communication between brain circuitry is a crucial step in the recovery of brain damage induced by traumatic injuries or neurological insults. In this work we present a study of real-time unidirectional communication between a spik...
Synapsins
Humans
Neural Networks, Computer
Microscopy, Fluorescence
In Vitro Techniques
Cerebral Cortex
Cells, Cultured
Light
Rats
Electrophysiology
Brain
Neurons
Models, Neurological
Computer Simulation
Video Recording
Electrodes, Implanted
Action Potentials
Animals
Immunohistochemistry
Optogenetics
Equipment Design
Neurotransmitter Agents
A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Apr 1, 2020
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) staining would save money, time, and reduce tissue co...
Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Mar 26, 2020
A deep learning-based image analysis could improve diagnostic accuracy and efficiency in pathology work. Recently, we proposed a deep learning-based detection algorithm for C4d immunostaining in renal allografts. The objective of this study is to ass...
A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.
European journal of radiology
Feb 13, 2020
PURPOSE: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic resonance imaging (MRI) but can be classified with immunohistochemical staining after surgery. In this study, a model to precisely immunohistochemical...
Computational analysis of morphological and molecular features in gastric cancer tissues.
Cancer medicine
Feb 3, 2020
Biological morphologies of cells and tissues represent their physiological and pathological conditions. The importance of quantitative assessment of morphological information has been highly recognized in clinical diagnosis and therapeutic strategies...
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