AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cell Line

Showing 101 to 110 of 223 articles

Clear Filters

Predicting the future direction of cell movement with convolutional neural networks.

PloS one
Image-based deep learning systems, such as convolutional neural networks (CNNs), have recently been applied to cell classification, producing impressive results; however, application of CNNs has been confined to classification of the current cell sta...

Magnetically Actuated Heterogeneous Microcapsule-Robot for the Construction of 3D Bioartificial Architectures.

ACS applied materials & interfaces
Core-shell microcapsules as one type of the most attractive carriers and reactors have been widely applied in the fields of drug screening and tissue engineering owing to their excellent biocompatibility and semi-permeability. Yet, the spatial organi...

Kinetics of -induced gene silencing can be predicted from combinations of epigenetic and genomic features.

Genome research
To initiate X-Chromosome inactivation (XCI), the long noncoding RNA mediates chromosome-wide gene silencing of one X Chromosome in female mammals to equalize gene dosage between the sexes. The efficiency of gene silencing is highly variable across g...

Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network.

Analytical chemistry
Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the c...

The cell line ontology-based representation, integration and analysis of cell lines used in China.

BMC bioinformatics
BACKGROUND: The Chinese National Infrastructure of Cell Line stores and distributes cell lines for biomedical research in China. This study aims to represent and integrate the information of NICR cell lines into the community-based Cell Line Ontology...

Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
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...

Learn to segment single cells with deep distance estimator and deep cell detector.

Computers in biology and medicine
Single cell segmentation is a critical and challenging step in cell imaging analysis. Traditional processing methods require time and labor to manually fine-tune parameters and lack parameter transferability between different situations. Recently, de...

Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN.

BMC bioinformatics
BACKGROUND: Cryo-electron tomography (cryo-ET) enables the 3D visualization of cellular organization in near-native state which plays important roles in the field of structural cell biology. However, due to the low signal-to-noise ratio (SNR), large ...

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

PloS one
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 ...

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

Journal of molecular graphics & modelling
BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for reproductive health. The role of FSHR in tumor progression as well as osteoporosis advancement has al...