AIMC Topic: Deep Learning

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A preliminary evaluation study of applying a deep learning image reconstruction algorithm in low-kilovolt scanning of upper abdomen.

Journal of X-ray science and technology
OBJECTIVE: To investigate feasibility of applying deep learning image reconstruction (DLIR) algorithm in a low-kilovolt enhanced scan of the upper abdomen.

[Development of Motion Artifact Generator for Deep Learning in Brain MRI].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: We focused on deep learning for a reduction of motion artifacts in MRI. It is difficult to collect a large number of images with and without motion artifacts from clinical images. The purpose of this study was to create motion artifact image...

Deep learning based analysis of sentiment dynamics in online cancer community forums: An experience.

Health informatics journal
Online health communities (OHC) provide various opportunities for patients with chronic or life-threatening illnesses, especially for cancer patients and survivors. A better understanding of the sentiment dynamics of patients in OHCs can help in the ...

Deep learning supported disease detection with multi-modality image fusion.

Journal of X-ray science and technology
Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing adequate complementary information from multi-modal medical images. These techniques enhance the effectiveness of medical disorder analysis and class...

Bionoi: A Voronoi Diagram-Based Representation of Ligand-Binding Sites in Proteins for Machine Learning Applications.

Methods in molecular biology (Clifton, N.J.)
Bionoi is a new software to generate Voronoi representations of ligand-binding sites in proteins for machine learning applications. Unlike many other deep learning models in biomedicine, Bionoi utilizes off-the-shelf convolutional neural network arch...

Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study.

The Lancet. Digital health
BACKGROUND: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of dee...

Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.)
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...

Robust deep learning pipeline for PVC beats localization.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Premature ventricular contraction (PVC) is among the most frequently occurring types of arrhythmias. Existing approaches for automated PVC identification suffer from a range of disadvantages related to hand-crafted features and benchmarki...