AIMC Topic: Deep Learning

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Deep-learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography.

Medical physics
PURPOSE: We are developing a computerized segmentation tool for the inner and outer bladder wall as a part of an image analysis pipeline for CT urography (CTU).

Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm.

Journal of cancer research and clinical oncology
PURPOSE: Oral cancer is a complex wide spread cancer, which has high severity. Using advanced technology and deep learning algorithm early detection and classification are made possible. Medical imaging technique, computer-aided diagnosis and detecti...

A Deep Learning-Based Approach to Reduce Rescan and Recall Rates in Clinical MRI Examinations.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: MR imaging rescans and recalls can create large hospital revenue loss. The purpose of this study was to develop a fast, automated method for assessing rescan need in motion-corrupted brain series.

Robust Single-Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features.

Sensors (Basel, Switzerland)
Face recognition using a single reference image per subject is challenging, above all when referring to a large gallery of subjects. Furthermore, the problem hardness seriously increases when the images are acquired in unconstrained conditions. In th...

Classification and Quantification of Emphysema Using a Multi-Scale Residual Network.

IEEE journal of biomedical and health informatics
Automated tissue classification is an essential step for quantitative analysis and treatment of emphysema. Although many studies have been conducted in this area, there still remain two major challenges. First, different emphysematous tissue appears ...

Using deep learning to identify translational research in genomic medicine beyond bench to bedside.

Database : the journal of biological databases and curation
Tracking scientific research publications on the evaluation, utility and implementation of genomic applications is critical for the translation of basic research to impact clinical and population health. In this work, we utilize state-of-the-art mach...

Combining relation extraction with function detection for BEL statement extraction.

Database : the journal of biological databases and curation
The BioCreative-V community proposed a challenging task of automatic extraction of causal relation network in Biological Expression Language (BEL) from the biomedical literature. Previous studies on this task largely used models induced from other re...

Deep Learning for Musculoskeletal Force Prediction.

Annals of biomedical engineering
Musculoskeletal models permit the determination of internal forces acting during dynamic movement, which is clinically useful, but traditional methods may suffer from slowness and a need for extensive input data. Recently, there has been interest in ...

Discovering functional impacts of miRNAs in cancers using a causal deep learning model.

BMC medical genomics
BACKGROUND: Micro-RNAs (miRNAs) play a significant role in regulating gene expression under physiological and pathological conditions such as cancers. However, it remains a challenging problem to discover the target messenger RNAs (mRNAs) of a miRNA ...

Deep learning for DNase I hypersensitive sites identification.

BMC genomics
BACKGROUND: The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources availab...