AIMC Topic: Deep Learning

Clear Filters Showing 27731 to 27740 of 28423 articles

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...

Accounting for data variability in multi-institutional distributed deep learning for medical imaging.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Sharing patient data across institutions to train generalizable deep learning models is challenging due to regulatory and technical hurdles. Distributed learning, where model weights are shared instead of patient data, presents an attract...

PlasGUN: gene prediction in plasmid metagenomic short reads using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: We present the first tool of gene prediction, PlasGUN, for plasmid metagenomic short-read data. The tool, developed based on deep learning algorithm of multiple input Convolutional Neural Network, demonstrates much better performance when te...

DEEPrior: a deep learning tool for the prioritization of gene fusions.

Bioinformatics (Oxford, England)
SUMMARY: In the last decade, increasing attention has been paid to the study of gene fusions. However, the problem of determining whether a gene fusion is a cancer driver or just a passenger mutation is still an open issue. Here we present DEEPrior, ...

Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection.

Investigative radiology
OBJECTIVES: The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).

Deep Residual Neural Networks Resolve Quartet Molecular Phylogenies.

Molecular biology and evolution
Phylogenetic inference is of fundamental importance to evolutionary as well as other fields of biology, and molecular sequences have emerged as the primary data for this task. Although many phylogenetic methods have been developed to explicitly take ...

[Progress in biomedical data analysis based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this...