AIMC Topic: Deep Learning

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Automated Evaluation of Upper Airway Obstruction Based on Deep Learning.

BioMed research international
OBJECTIVES: This study is aimed at developing a screening tool that could evaluate the upper airway obstruction on lateral cephalograms based on deep learning.

Development and Validation of Deep Learning Models for the Multiclassification of Reflux Esophagitis Based on the Los Angeles Classification.

Journal of healthcare engineering
This study is to evaluate the feasibility of deep learning (DL) models in the multiclassification of reflux esophagitis (RE) endoscopic images, according to the Los Angeles (LA) classification for the first time. The images were divided into three gr...

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

Magma (New York, N.Y.)
OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is requi...

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton ( H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acqui...

Quantifying Inflammatory Response and Drug-Aided Resolution in an Atopic Dermatitis Model with Deep Learning.

The Journal of investigative dermatology
Noninvasive quantification of dermal diseases aids efficacy studies and paves the way for broader enrollment in clinical studies across varied demographics. Related to atopic dermatitis, accurate quantification of the onset and resolution of inflamma...

Technical note: Progressive deep learning: An accelerated training strategy for medical image segmentation.

Medical physics
BACKGROUND: Recent advancements in Deep Learning (DL) methodologies have led to state-of-the-art performance in a wide range of applications especially in object recognition, classification, and segmentation of medical images. However, training moder...

Development, validation, and evaluation of a deep learning model to screen cyclin-dependent kinase 12 inhibitors in cancers.

European journal of medicinal chemistry
Deep learning-based in silico alternatives have been demonstrated to be of significant importance in the acceleration of the drug discovery process and enhancement of success rates. Cyclin-dependent kinase 12 (CDK12) is a transcription-related cyclin...

Diagnostic performance of deep learning-based vessel extraction and stenosis detection on coronary computed tomography angiography for coronary artery disease: a multi-reader multi-case study.

La Radiologia medica
BACKGROUND: Post-processing and interpretation of coronary CT angiography (CCTA) imaging are time-consuming and dependent on the reader's experience. An automated deep learning (DL)-based imaging reconstruction and diagnosis system was developed to i...

A Deep Learning-Based Semantic Segmentation Model Using MCNN and Attention Layer for Human Activity Recognition.

Sensors (Basel, Switzerland)
With the development of wearable devices such as smartwatches, several studies have been conducted on the recognition of various human activities. Various types of data are used, e.g., acceleration data collected using an inertial measurement unit se...

RNA independent fragment partition method based on deep learning for RNA secondary structure prediction.

Scientific reports
The non-coding RNA secondary structure largely determines its function. Hence, accuracy in structure acquisition is of great importance. Currently, this acquisition primarily relies on various computational methods. The prediction of the structures o...