AIMC Topic: Middle Aged

Clear Filters Showing 12421 to 12430 of 17155 articles

Sex Determination of 3D Skull Based on a Novel Unsupervised Learning Method.

Computational and mathematical methods in medicine
In law enforcement investigation cases, sex determination from skull morphology is one of the important steps in establishing the identity of an individual from unidentified human skeleton. To our knowledge, existing studies of sex determination of t...

EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces.

Journal of neural engineering
OBJECTIVE: Brain-computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given...

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

BMC medical informatics and decision making
BACKGROUND: Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthca...

Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors.

Scientific reports
Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this study, we proposed deep-learned 3D BB imaging with an auto-labelling techniq...

An Intelligent Parkinson's Disease Diagnostic System Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach.

Computational and mathematical methods in medicine
Parkinson's disease (PD) is a common neurodegenerative disease, which has attracted more and more attention. Many artificial intelligence methods have been used for the diagnosis of PD. In this study, an enhanced fuzzy -nearest neighbor (FKNN) method...

Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram.

Physiological measurement
OBJECTIVE: In this paper, we propose a convolutional neural network (CNN)-based deep learning architecture for multiclass classification of obstructive sleep apnea and hypopnea (OSAH) using single-lead electrocardiogram (ECG) recordings. OSAH is the ...

Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
PURPOSE:  In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by co...

Comparison of Models for Predicting Quality of Life After Surgical Resection of Hepatocellular Carcinoma: a Prospective Study.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: The essential issue of internal validity has not been adequately addressed in prediction models such as artificial neural network (ANN), support vector machine (SVM), Gaussian process regression (GPR), and multiple linear regression (MLR)...

Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning.

American journal of ophthalmology
PURPOSE: Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine learning-based index for glau...

Quantitative susceptibility mapping using deep neural network: QSMnet.

NeuroImage
Deep neural networks have demonstrated promising potential for the field of medical image reconstruction, successfully generating high quality images for CT, PET and MRI. In this work, an MRI reconstruction algorithm, which is referred to as quantita...