AIMC Topic: Immunohistochemistry

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LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.

Cancer research and treatment Dec 29, 2020
PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely s...
Prospective Studies Prognosis Retrospective Studies Female Aged Humans Machine Learning Lymph Nodes Lymphocytes, Tumor-Infiltrating Lymphatic Metastasis Neoplasm Staging Immunohistochemistry Colorectal Neoplasms Male Risk Assessment ROC Curve
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Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning.

EBioMedicine Nov 7, 2020
BACKGROUND: Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that effectively address its heterogeneity. To meet these shortcomings, we show that Diversit...
Immunohistochemistry Disease Susceptibility Animals Humans Tuberculosis Computational Biology Biomarkers Male Machine Learning Mycobacterium tuberculosis Deep Learning Algorithms Disease Models, Animal Molecular Imaging Image Processing, Computer-Assisted Prognosis Female Reproducibility of Results
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The role of artificial intelligence to quantify the tumour-stroma ratio for survival in colorectal cancer.

EBioMedicine Oct 21, 2020
Biomarkers Prognosis Colorectal Neoplasms Tumor Microenvironment Neoplasm Staging Stromal Cells Humans Immunohistochemistry Artificial Intelligence Image Processing, Computer-Assisted Algorithms Cancer-Associated Fibroblasts
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Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.

EBioMedicine Oct 8, 2020
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...
Female Aged Adult Colorectal Neoplasms Humans Artificial Intelligence Prognosis Retrospective Studies Neoplasm Staging Neoplasm Grading Cell Count Stromal Cells Immunohistochemistry Tumor Microenvironment Male Middle Aged Cancer-Associated Fibroblasts Proportional Hazards Models
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Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma.

Virchows Archiv : an international journal of pathology Sep 26, 2020
In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slide...
Humans In Situ Hybridization, Fluorescence Image Interpretation, Computer-Assisted Immunohistochemistry Proof of Concept Study Translocation, Genetic Antigens, CD20 Proto-Oncogene Proteins c-myc Deep Learning Phenotype Staining and Labeling Genetic Predisposition to Disease Reproducibility of Results Predictive Value of Tests Biomarkers, Tumor Microscopy Lymphoma, Large B-Cell, Diffuse
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Deep learning quantification of percent steatosis in donor liver biopsy frozen sections.

EBioMedicine Sep 24, 2020
BACKGROUND: Pathologist evaluation of donor liver biopsies provides information for accepting or discarding potential donor livers. Due to the urgent nature of the decision process, this is regularly performed using frozen sectioning at the time of b...
Image Processing, Computer-Assisted Fatty Liver Living Donors Biopsy Molecular Sequence Annotation Frozen Sections Liver Transplantation Immunohistochemistry Neural Networks, Computer Algorithms Severity of Illness Index Deep Learning Humans
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The Use of Quantitative Digital Pathology to Measure Proteoglycan and Glycosaminoglycan Expression and Accumulation in Healthy and Diseased Tissues.

The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society Sep 16, 2020
Advances in reagents, methodologies, analytic platforms, and tools have resulted in a dramatic transformation of the research pathology laboratory. These advances have increased our ability to efficiently generate substantial volumes of data on the e...
Immunohistochemistry Image Processing, Computer-Assisted Proteoglycans Glycosaminoglycans In Situ Hybridization, Fluorescence Humans Artificial Intelligence
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Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.

Radiologic clinics of North America Sep 14, 2020
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...
Clinical Decision-Making Female Male Ultrasonography, Doppler Incidence Biopsy, Needle Incidental Findings Diagnostic Imaging Humans Artificial Intelligence Positron Emission Tomography Computed Tomography Thyroid Neoplasms Thyroid Nodule United States Radiologists Magnetic Resonance Imaging Practice Guidelines as Topic Immunohistochemistry
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Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

Journal of bioinformatics and computational biology Aug 21, 2020
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...
Algorithms Flow Cytometry Databases, Factual Colorectal Neoplasms Immunohistochemistry Tumor Microenvironment Neutrophils Support Vector Machine CD8-Positive T-Lymphocytes Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans
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Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.

Diagnostic pathology Jul 28, 2020
BACKGROUND: Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to...
Pancreatic Neoplasms Humans Carcinoma, Pancreatic Ductal Biomarkers, Tumor Immunohistochemistry Deep Learning Image Processing, Computer-Assisted
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