Practice Management

ncRDense: A novel computational approach for classification of non-coding RNA family by deep learning.

With the rapidly growing importance of biological research, non-coding RNAs (ncRNA) attract more attention in biology and bioinformatics. They play vital roles in biological processes such as transcription and translation. Classification of ncRNAs is essential to our understanding of disease mechanisms and treatment design. Many approaches to ncRNA classification have been developed, several of wh...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (ICD)-10 on Diseases of the skin and subcutaneous tissue, which is now globally used for classification of skin disease. This study was aimed to develo...

Joint representation of color and form in convolutional neural networks: A stimulus-rich network perspective.

To interact with real-world objects, any effective visual system must jointly code the unique features defining each object. Despite decades of neuros...

Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs.

The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experim...

Blind Recognition of Forward Error Correction Codes Based on Recurrent Neural Network.

Forward error correction coding is the most common way of channel coding and the key point of error correction coding. Therefore, the recognition of w...

ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion.

The dysregulation and mutation of long non-coding RNAs (lncRNAs) have been proved to result in a variety of human diseases. Identifying potential dise...

A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations.

BACKGROUND: Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and ...

Methodology for comprehensive cell-level analysis of wound healing experiments using deep learning in MATLAB.

BACKGROUND: Endothelial healing after deployment of cardiovascular devices is particularly important in the context of clinical outcome. It is therefo...

A supervised clustering MCMC methodology for large categorical feature spaces.

There is a well-established tradition within the statistics literature that explores different techniques for reducing the dimensionality of large fea...

Role of Regulatory Non-Coding RNAs in Aggressive Thyroid Cancer: Prospective Applications of Neural Network Analysis.

Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, whereas anaplastic thyroid carcinoma (ATC) is a leth...

Deep learning applied to electroencephalogram data in mental disorders: A systematic review.

In recent medical research, tremendous progress has been made in the application of deep learning (DL) techniques. This article systematically reviews...

Hybrid dilation and attention residual U-Net for medical image segmentation.

Medical image segmentation is a typical task in medical image processing and critical foundation in medical image analysis. U-Net is well-liked in med...

Is machine learning and automatic classification of swimming data what unlocks the power of inertial measurement units in swimming?

Researchers have heralded the power of inertial sensors as a reliable swimmer-centric monitoring technology, however, regular uptake of this technolog...

Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.

Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage...

A comparison of natural language processing to ICD-10 codes for identification and characterization of pulmonary embolism.

INTRODUCTION: The 10th revision of the International Classification of Diseases (ICD-10) codes is frequently used to identify pulmonary embolism (PE) ...

Progressive Transmission of Medical Images via a Bank of Generative Adversarial Networks.

The healthcare sector is currently undergoing a major transformation due to the recent advances in deep learning and artificial intelligence. Despite ...

RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

Non-coding RNAs (ncRNAs) are important players in the cellular regulation of organisms from different kingdoms. One of the key steps in ncRNAs researc...

Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering.

In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filt...

ncRFP: A Novel end-to-end Method for Non-Coding RNAs Family Prediction Based on Deep Learning.

Evidence has accumulated enough to prove non-coding RNAs (ncRNAs) play important roles in cellular biological processes and disease pathogenesis. High...

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks.

A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonide...