Practice Management

Latest AI and machine learning research in practice management for healthcare professionals.

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Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning.

Over the past years, large consortia have been established to fuel the sequencing of whole genomes o...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hypera...

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 att...

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...

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 featur...

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 characterizati...

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 ...

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 var...

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...

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 oft...

A supervised clustering MCMC methodology for large categorical feature spaces.

There is a well-established tradition within the statistics literature that explores different techn...

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, wh...

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 (D...

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 ...

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 tec...

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...

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 fr...

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 d...

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 differen...

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 informat...

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 b...

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