AIMC Topic: Deep Learning

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A deep learning system for quantitative assessment of microvascular abnormalities in nailfold capillary images.

Rheumatology (Oxford, England)
OBJECTIVES: Nailfold capillaroscopy is key to timely diagnosis of SSc, but is often not used in rheumatology clinics because the images are difficult to interpret. We aimed to develop and validate a fully automated image analysis system to fill this ...

Single-shot multispectral quantitative phase imaging of biological samples using deep learning.

Applied optics
Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly...

Automated Classification of Inherited Retinal Diseases in Optical Coherence Tomography Images Using Few-shot Learning.

Biomedical and environmental sciences : BES
OBJECTIVE: To develop a few-shot learning (FSL) approach for classifying optical coherence tomography (OCT) images in patients with inherited retinal disorders (IRDs).

DiMo: discovery of microRNA motifs using deep learning and motif embedding.

Briefings in bioinformatics
MicroRNAs are small regulatory RNAs that decrease gene expression after transcription in various biological disciplines. In bioinformatics, identifying microRNAs and predicting their functionalities is critical. Finding motifs is one of the most well...

Graph deep learning enabled spatial domains identification for spatial transcriptomics.

Briefings in bioinformatics
Advancing spatially resolved transcriptomics (ST) technologies help biologists comprehensively understand organ function and tissue microenvironment. Accurate spatial domain identification is the foundation for delineating genome heterogeneity and ce...

Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review.

Briefings in bioinformatics
CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9) is a popular and effective two-component technology used for targeted genetic manipulation. It is currently the most versatile and accurate method...

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications.

Current pharmaceutical design
It takes an average of 10-15 years to uncover and develop a new drug, and the process is incredibly time-consuming, expensive, difficult, and ineffective. In recent years the dramatic changes in the field of artificial intelligence (AI) have helped t...

UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity.

Briefings in bioinformatics
Identification of potent peptides through model prediction can reduce benchwork in wet experiments. However, the conventional process of model buildings can be complex and time consuming due to challenges such as peptide representation, feature selec...