AIMC Topic: Male

Clear Filters Showing 17941 to 17950 of 27433 articles

Deep learning for automated segmentation of pelvic muscles, fat, and bone from CT studies for body composition assessment.

Skeletal radiology
OBJECTIVE: To develop a deep convolutional neural network (CNN) to automatically segment an axial CT image of the pelvis for body composition measures. We hypothesized that a deep CNN approach would achieve high accuracy when compared to manual segme...

A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments.

Neural computation
In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled envi...

Towards On-Demand Virtual Physical Therapist: Machine Learning-Based Patient Action Understanding, Assessment and Task Recommendation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this paper, we propose a machine learning-based virtual physical therapist (PT) system to enable personalized remote training for patients with Parkinson's disease (PD). Three physical therapy tasks with multiple difficulty levels are selected to ...

Improved diagnostic accuracy for myocardial perfusion imaging using artificial neural networks on different input variables including clinical and quantification data.

Revista espanola de medicina nuclear e imagen molecular
OBJECTIVE: Diagnostic accuracy of myocardial perfusion imaging (MPI) is not optimal to predict the result of angiography. The current study aimed at investigating the application of artificial neural network (ANN) to integrate the clinical data with ...

Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI.

Magnetic resonance in medicine
PURPOSE: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted MRI (DW-MRI) data and evaluates its performance.

Identifying key gait features associated with the radiological grade of knee osteoarthritis.

Osteoarthritis and cartilage
PURPOSE: Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. This study assessed key features that can be used as mechanical biomarkers for KOA severity and progression. The identified features were validated statistically...

Using street view data and machine learning to assess how perception of neighborhood safety influences urban residents' mental health.

Health & place
Previous studies have shown that perceptions of neighborhood safety are associated with various mental health outcomes. However, scant attention has been paid to the mediating pathways by which perception of neighborhood safety affects mental health....

A robotic neck brace to characterize head-neck motion and muscle electromyography in subjects with amyotrophic lateral sclerosis.

Annals of clinical and translational neurology
OBJECTIVE: This paper presents the first study where a dynamic neck brace was used to characterize the head motion of ALS patients while concurrently recording the surface electromyography (EMG) of the neck muscles.

Machine learning applications in prostate cancer magnetic resonance imaging.

European radiology experimental
With this review, we aimed to provide a synopsis of recently proposed applications of machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI). After defining the difference between ML and classical rule-based algorith...