AIMC Topic: Cell Line, Tumor

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Detecting mitotic cells in HEp-2 images as anomalies via one class classifier.

Computers in biology and medicine Jun 17, 2019
We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided Diagnosis (CAD) system for Anti-Nuclear Antibodies (ANA) detection. In the proposed work, due to unique characteristics (the rare occurrence) of the ...
Humans Neural Networks, Computer Support Vector Machine Autoimmune Diseases Mitosis Antibodies, Antinuclear Cell Line, Tumor ROC Curve Image Processing, Computer-Assisted
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Prediction of Drug Target Sensitivity in Cancer Cell Lines Using Apache Spark.

Journal of computational biology : a journal of computational molecular cell biology May 23, 2019
Female Breast Neoplasms Cell Line, Tumor Humans Machine Learning Software Drug Development
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Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network.

IEEE transactions on medical imaging May 22, 2019
Automatic and accurate classification of apoptosis, or programmed cell death, will facilitate cell biology research. The state-of-the-art approaches in apoptosis classification use deep convolutional neural networks (CNNs). However, these networks ar...
Cytological Techniques Cells Microscopy, Phase-Contrast Cell Line, Tumor Image Processing, Computer-Assisted Apoptosis Humans Neural Networks, Computer
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Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.

ChemMedChem May 16, 2019
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...
Stereoisomerism Acetylcholinesterase Cholinesterase Inhibitors Galantamine Neuroprotective Agents Molecular Docking Simulation Biological Products Drug Design Molecular Structure Cell Line, Tumor Drug Evaluation, Preclinical Alzheimer Disease Ligands Humans Machine Learning
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An ontology for representing hematologic malignancies: the cancer cell ontology.

BMC bioinformatics Apr 25, 2019
BACKGROUND: Within the cancer domain, ontologies play an important role in the integration and annotation of data in order to support numerous biomedical tools and applications. This work seeks to leverage existing standards in immunophenotyping cell...
Biological Ontologies Cell Line, Tumor Neoplastic Stem Cells Humans Immunophenotyping Machine Learning Hematologic Neoplasms
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Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Apr 22, 2019
Robust and reproducible profiling of cell lines is essential for phenotypic screening assays. The goals of this study were to determine robust and reproducible optical phase signatures of cell lines for classification with machine learning and to cor...
Cell Line Epithelial Cells Microscopy Chemotaxis Holography Mesoderm Cell Line, Tumor Image Processing, Computer-Assisted Cell Movement Humans Machine Learning
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Machine Learning Based Real-Time Image-Guided Cell Sorting and Classification.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Apr 8, 2019
Cell classification based on phenotypical, spatial, and genetic information greatly advances our understanding of the physiology and pathology of biological systems. Technologies derived from next generation sequencing and fluorescent activated cell ...
Gamma Rays Proteins Flow Cytometry Dogs Madin Darby Canine Kidney Cells Humans Animals Cell Membrane Machine Learning Computer Systems Green Fluorescent Proteins Algorithms Cell Line, Tumor
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Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2019
DNA methylation plays an important role in the regulation of some biological processes. Up to now, with the development of machine learning models, there are several sequence-based deep learning models designed to predict DNA methylation states, whic...
DNA Methylation DNA High-Throughput Nucleotide Sequencing Histone Code Cell Line, Tumor Computational Biology Sequence Analysis, DNA Humans Deep Learning
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Bagging and deep learning in optimal individualized treatment rules.

Biometrics Mar 29, 2019
An ENsemble Deep Learning Optimal Treatment (EndLot) approach is proposed for personalized medicine problems. The statistical framework of the proposed method is based on the outcome weighted learning (OWL) framework which transforms the optimal deci...
Cell Line, Tumor Decision Support Systems, Clinical Databases as Topic Humans Neural Networks, Computer Computer Simulation Precision Medicine Deep Learning
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Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Journal of medical systems Mar 27, 2019
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two...
Ovarian Neoplasms Female Humans Image Interpretation, Computer-Assisted Sensitivity and Specificity Anisotropy Machine Learning Optical Imaging Cell Line, Tumor Algorithms
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