AIMC Topic: Cell Line, Tumor

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Convolutional neural network for cell classification using microscope images of intracellular actin networks.

PloS one Mar 13, 2019
Automated cell classification is an important yet a challenging computer vision task with significant benefits to biomedicine. In recent years, there have been several studies attempted to build an artificial intelligence-based cell classifier using ...
Humans Neural Networks, Computer Actins Cytoplasm Cytoskeleton Cell Line Models, Statistical MCF-7 Cells Microscopy, Fluorescence Breast Automation Pattern Recognition, Automated Reproducibility of Results Breast Neoplasms Machine Learning Cell Line, Tumor Image Processing, Computer-Assisted Algorithms Female
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Plasmonic MoO nanoparticles incorporated in Prussian blue frameworks exhibit highly efficient dual photothermal/photodynamic therapy.

Journal of materials chemistry. B Feb 21, 2019
Development of near infrared (NIR) light-responsive nanomaterials for high performance multimodal phototherapy within a single nanoplatform is still challenging in technology and biomedicine. Herein, a new phototherapeutic nanoagent based on FDA-appr...
Reactive Oxygen Species Lasers Cell Line, Tumor Humans Nanoparticles Oxides Molybdenum Female Triple Negative Breast Neoplasms Coloring Agents Nanocomposites Animals Mice, Inbred BALB C Phototherapy Ferrocyanides
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Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

Computational biology and chemistry Feb 16, 2019
BACKGROUND/AIM: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline m...
Cell Proliferation Gallic Acid PC-3 Cells Support Vector Machine Algorithms Drug Screening Assays, Antitumor Humans Dose-Response Relationship, Drug Antineoplastic Agents Structure-Activity Relationship Artificial Intelligence Time Factors Models, Molecular Machine Learning Cell Line, Tumor Molecular Structure
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Objective risk stratification of prostate cancer using machine learning and radiomics applied to multiparametric magnetic resonance images.

Scientific reports Feb 7, 2019
Multiparametric magnetic resonance imaging (mpMRI) has become increasingly important for the clinical assessment of prostate cancer (PCa), but its interpretation is generally variable due to its relatively subjective nature. Radiomics and classificat...
Machine Learning Reproducibility of Results Mice Risk Assessment Animals Prostatic Neoplasms Cell Line, Tumor Male Immunohistochemistry Humans Image Processing, Computer-Assisted Multiparametric Magnetic Resonance Imaging
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Predicting drug response of tumors from integrated genomic profiles by deep neural networks.

BMC medical genomics Jan 31, 2019
BACKGROUND: The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent study screened for the response of a thousand human cancer ...
Cell Line, Tumor Genomics Mutation Docetaxel Benzothiazoles Naphthyridines Humans Antineoplastic Agents Transcriptome Deep Learning
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Evaluation of Machine Learning Classifiers to Predict Compound Mechanism of Action When Transferred across Distinct Cell Lines.

SLAS discovery : advancing life sciences R & D Jan 29, 2019
Multiparametric high-content imaging assays have become established to classify cell phenotypes from functional genomic and small-molecule library screening assays. Several groups have implemented machine learning classifiers to predict the mechanism...
Cytological Techniques Neural Networks, Computer Machine Learning Cell Line, Tumor Humans
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Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome.

BMC bioinformatics Jan 5, 2019
BACKGROUND: To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data...
Humans Machine Learning Algorithms Proteome Databases, Protein Histocompatibility Antigens Class I Gene Expression Regulation Reproducibility of Results Peptides Cell Line, Tumor
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In vitro bioactivity and degradation behaviour of β-wollastonite derived from natural waste.

Materials science & engineering. C, Materials for biological applications Dec 29, 2018
Calcium silicate ceramics, in particular wollastonite (CaSiO), is the most commonly used bioactive material for bone regeneration and repairing applications. The present study aims to synthesize cost effective wollastonite using natural waste materia...
Spectroscopy, Fourier Transform Infrared Cell Survival Biocompatible Materials Calcium Compounds Humans Cell Line, Tumor Durapatite X-Ray Diffraction
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Glucose-holmium for radiotherapy: Characterization and in vitro assays.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine Dec 21, 2018
BACKGROUND: The existence of saccharide-holmium complexes, containing mono or polysaccharide molecules, is an attractive hypothesis toward a radiation therapy (RT) with beta-emitters targeting high glucose metabolic human sites. To exam such hypothes...
Neutron Activation Analysis Radiopharmaceuticals Female Humans Spectrometry, Mass, Electrospray Ionization Radioisotopes Breast Neoplasms Holmium Cell Line, Tumor Glucose
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Predicting tumor cell line response to drug pairs with deep learning.

BMC bioinformatics Dec 21, 2018
BACKGROUND: The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity.
Deep Learning Cell Line, Tumor Humans United States Drug Evaluation, Preclinical Neural Networks, Computer National Cancer Institute (U.S.)
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