AIMC Topic: Neural Networks, Computer

Clear Filters Showing 30201 to 30210 of 31376 articles

Clinical trial cohort selection based on multi-level rule-based natural language processing system.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identifying patients who meet selection criteria for clinical trials is typically challenging and time-consuming. In this article, we describe our clinical natural language processing (NLP) system to automatically assess patients' eligibil...

Enhancing clinical concept extraction with contextual embeddings.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and represe...

Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Our objective is to develop algorithms for encoding clinical text into representations that can be used for a variety of phenotyping tasks.

ML-Net: multi-label classification of biomedical texts with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In multi-label text classification, each textual document is assigned 1 or more labels. As an important task that has broad applications in biomedicine, a number of different computational methods have been proposed. Many of these methods,...

Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: HIV infection risk can be estimated based on not only individual features but also social network information. However, there have been insufficient studies using n machine learning methods that can maximize the utility of such information...

ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Contact-map of a protein sequence dictates the global topology of structural fold. Accurate prediction of the contact-map is thus essential to protein 3D structure prediction, which is particularly useful for the protein sequences that do...

HiCNN: a very deep convolutional neural network to better enhance the resolution of Hi-C data.

Bioinformatics (Oxford, England)
MOTIVATION: High-resolution Hi-C data are indispensable for the studies of three-dimensional (3D) genome organization at kilobase level. However, generating high-resolution Hi-C data (e.g. 5 kb) by conducting Hi-C experiments needs millions of mammal...

Biomedical image augmentation using Augmentor.

Bioinformatics (Oxford, England)
MOTIVATION: Image augmentation is a frequently used technique in computer vision and has been seeing increased interest since the popularity of deep learning. Its usefulness is becoming more and more recognized due to deep neural networks requiring l...

A learning-based framework for miRNA-disease association identification using neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: A microRNA (miRNA) is a type of non-coding RNA, which plays important roles in many biological processes. Lots of studies have shown that miRNAs are implicated in human diseases, indicating that miRNAs might be potential biomarkers for va...

Automated Taxonomic Identification of Insects with Expert-Level Accuracy Using Effective Feature Transfer from Convolutional Networks.

Systematic biology
Rapid and reliable identification of insects is important in many contexts, from the detection of disease vectors and invasive species to the sorting of material from biodiversity inventories. Because of the shortage of adequate expertise, there has ...