AIMC Topic: Fluorescent Antibody Technique

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A machine learning approach toward automating spatial identification of LAG3+/CD3+ cells in ulcerative colitis.

Scientific reports Dec 8, 2023
Over the past decade, automation of digital image analysis has become commonplace in both research and clinical settings. Spurred by recent advances in artificial intelligence and machine learning (AI/ML), tissue sub-compartments and cellular phenoty...
Humans Biomarkers Colitis, Ulcerative Fluorescent Antibody Technique Artificial Intelligence Machine Learning Algorithms
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Deep multi-task learning for nephropathy diagnosis on immunofluorescence images.

Computer methods and programs in biomedicine Aug 16, 2023
BACKGROUND AND OBJECTIVE: As an advanced technique, immunofluorescence (IF) is one of the most widely-used medical image for nephropathy diagnosis, due to its ease of acquisition with low cost. In practice, the clinically collected IF images are comm...
Databases, Factual Fluorescent Antibody Technique Humans Neural Networks, Computer
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A Deep-Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area Based on a Six-Colour Multiplex Immunofluorescence Panel.

Cells Apr 2, 2023
Liver cancer is one of the most frequently diagnosed and fatal cancers worldwide, with hepatocellular carcinoma (HCC) being the most common primary liver cancer. Hundreds of studies involving thousands of patients have now been analysed across differ...
Humans Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Color Fluorescent Antibody Technique
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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...
Humans Artificial Intelligence B7-H1 Antigen Immunohistochemistry Fluorescent Antibody Technique Biomarkers, Tumor Neoplasms
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Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Scientific reports Mar 15, 2022
Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline t...
Neural Networks, Computer Software Animals Humans Fluorescent Antibody Technique Image Processing, Computer-Assisted Mice Staining and Labeling
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Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation.

IEEE transactions on medical imaging Jun 30, 2021
Separating and labeling each nuclear instance (instance-aware segmentation) is the key challenge in nuclear image segmentation. Deep Convolutional Neural Networks have been demonstrated to solve nuclear image segmentation tasks across different imagi...
Fluorescent Antibody Technique Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted
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A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.

Acta cytologica Jun 2, 2021
INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assist cytologists in distiguishing metastatic cancer cells from reactive mesothelial cells. However, evaluating biomarker expression visually may be chal...
Cytodiagnosis Pleural Effusion, Malignant Deep Learning Fluorescent Antibody Technique Adenocarcinoma Microscopy, Fluorescence Humans Reproducibility of Results Image Processing, Computer-Assisted Diagnosis, Differential Retrospective Studies Biomarkers, Tumor Feasibility Studies Predictive Value of Tests Diagnosis, Computer-Assisted
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Deep learning-based predictive identification of neural stem cell differentiation.

Nature communications May 10, 2021
The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is...
Neural Stem Cells Nerve Growth Factors Fluorescent Antibody Technique Neurogenesis Oligodendroglia Neurons Microscopy, Electron, Transmission Animals Deep Learning Nanoparticles Rats Astrocytes Hormones Neural Networks, Computer Cells, Cultured Computer Simulation
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Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Scientific reports Mar 24, 2021
Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to ...
Mesenchymal Stem Cells Molecular Imaging Fluorescent Antibody Technique Image Processing, Computer-Assisted Gene Expression Artificial Intelligence Staining and Labeling Flow Cytometry Biomarkers Computational Biology Gene Expression Profiling
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Astrocyte regional heterogeneity revealed through machine learning-based glial neuroanatomical assays.

The Journal of comparative neurology Mar 8, 2021
Evaluation of reactive astrogliosis by neuroanatomical assays represents a common experimental outcome for neuroanatomists. The literature demonstrates several conflicting results as to the accuracy of such measures. We posited that the diverging res...
Machine Learning Gliosis Animals Mice Fluorescent Antibody Technique Image Processing, Computer-Assisted Microscopy, Confocal Astrocytes
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