AIMC Topic: Female

Clear Filters Showing 17901 to 17910 of 29210 articles

Applying cascaded convolutional neural network design further enhances automatic scoring of arthritis disease activity on ultrasound images from rheumatoid arthritis patients.

Annals of the rheumatic diseases
OBJECTIVES: We have previously shown that neural network technology can be used for scoring arthritis disease activity in ultrasound images from rheumatoid arthritis (RA) patients, giving scores according to the EULAR-OMERACT grading system. We have ...

Effects of gait exercise assist robot (GEAR) on subjects with chronic stroke: A randomized controlled pilot trial.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: The aim of this study was to investigate whether gait training using the Gait Exercise Assist Robot (GEAR) is more effective for improving gait ability than treadmill gait training in chronic stroke subjects.

A case-based ensemble learning system for explainable breast cancer recurrence prediction.

Artificial intelligence in medicine
Significant progress has been achieved in recent years in the application of artificial intelligence (AI) for medical decision support. However, many AI-based systems often only provide a final prediction to the doctor without an explanation of its u...

Strain Curve Classification Using Supervised Machine Learning Algorithm with Physiologic Constraints.

Ultrasound in medicine & biology
Speckle tracking echocardiography (STE) enables quantification of myocardial deformation by a generation of spatiotemporal strain curves or time-strain curves (TSCs). Currently, only assessment of peak global longitudinal strain is employed in clinic...

Dyslexia Diagnosis by EEG Temporal and Spectral Descriptors: An Anomaly Detection Approach.

International journal of neural systems
Diagnosis of learning difficulties is a challenging goal. There are huge number of factors involved in the evaluation procedure that present high variance among the population with the same difficulty. Diagnosis is usually performed by scoring subjec...

Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on F-Florbetapir PET Using ADNI Data.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Cortical amyloid quantification on PET by using the standardized uptake value ratio is valuable for research studies and clinical trials in Alzheimer disease. However, it is resource intensive, requiring co-registered MR imagi...

Identifying psychosis spectrum youth using support vector machines and cerebral blood perfusion as measured by arterial spin labeled fMRI.

NeuroImage. Clinical
Altered cerebral blood flow (CBF), as measured by arterial spin labelling (ASL), has been observed in several psychiatric conditions, but is a generally underutilized MRI technique, especially in the study of psychosis spectrum (PS) symptoms. We aime...

Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

Clinical EEG and neuroscience
The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation of both structural and functional connections of the brain and the effect...

Altered resting-state functional connectivity and effective connectivity of the habenula in irritable bowel syndrome: A cross-sectional and machine learning study.

Human brain mapping
Irritable bowel syndrome (IBS) is a disorder involving dysfunctional brain-gut interactions characterized by chronic recurrent abdominal pain, altered bowel habits, and negative emotion. Previous studies have linked the habenula to the pathophysiolog...

Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium.

European journal of radiology
PURPOSE: Coronary artery calcium (CAC) score has shown to be an accurate predictor of future cardiovascular events. Early detection by CAC scoring might reduce the number of deaths by cardiovascular disease (CVD). Automatically excluding scans which ...