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A deep learning based pipeline for optical coherence tomography angiography.
Journal of biophotonics
Jul 1, 2019
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denois...
Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.
Journal of chemical information and modeling
Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
A Machine Learning Approach to Characterize the Modulation of the Hippocampal Rhythms Via Optogenetic Stimulation of the Medial Septum.
International journal of neural systems
Jun 27, 2019
The medial septum (MS) is a potential target for modulating hippocampal activity. However, given the multiple cell types involved, the changes in hippocampal neural activity induced by MS stimulation have not yet been fully characterized. We combined...
Analysis and prediction of human acetylation using a cascade classifier based on support vector machine.
BMC bioinformatics
Jun 17, 2019
BACKGROUND: Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify acetylation sites in protein...
Automated Machine Learning Diagnostic Support System as a Computational Biomarker for Detecting Drug-Induced Liver Injury Patterns in Whole Slide Liver Pathology Images.
Assay and drug development technologies
May 31, 2019
in vivor p R.
Q&A: Understanding the composition of behavior.
BMC biology
May 29, 2019
Understanding the brain requires understanding behavior. New machine vision and learning techniques are poised to revolutionize our ability to analyze behaviors exhibited by animals in the laboratory. Here we describe one such method, Motion Sequenci...
High-field mr diffusion-weighted image denoising using a joint denoising convolutional neural network.
Journal of magnetic resonance imaging : JMRI
Apr 22, 2019
BACKGROUND: Low signal-to-noise ratio (SNR) has been a major limiting factor for the application of higher-resolution diffusion-weighted imaging (DWI). Most of the conventional denoising models suffer from the drawbacks of shallow feature extraction ...
SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species.
PLoS computational biology
Apr 18, 2019
Understanding sleep and its perturbation by environment, mutation, or medication remains a central problem in biomedical research. Its examination in animal models rests on brain state analysis via classification of electroencephalographic (EEG) sign...
Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN.
BMC bioinformatics
Mar 29, 2019
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 ...
Comparison between two programs for image analysis, machine learning and subsequent classification.
Tissue & cell
Mar 27, 2019
In the early 1950s, flow cytometry was developed as the first method for automated quantitative cellular analysis. In the early 1990s, the first equipment for image cytometry (laser scanning cytometry, LSC) became commercially available. As flow cyto...
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