AIMC Topic: Female

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Predicting individual responses to the electroconvulsive therapy with hippocampal subfield volumes in major depression disorder.

Scientific reports
Electroconvulsive therapy (ECT) is one of the most effective treatments for major depression disorder (MDD). ECT can induce neurogenesis and synaptogenesis in hippocampus, which contains distinct subfields, e.g., the cornu ammonis (CA) subfields, a g...

Effective Pneumothorax Detection for Chest X-Ray Images Using Local Binary Pattern and Support Vector Machine.

Journal of healthcare engineering
Automatic image segmentation and feature analysis can assist doctors in the treatment and diagnosis of diseases more accurately. Automatic medical image segmentation is difficult due to the varying image quality among equipment. In this paper, the au...

Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients.

Journal of healthcare engineering
Motor imagery-based brain-computer interfaces (BCI) have shown potential for the rehabilitation of stroke patients; however, low performance has restricted their application in clinical environments. Therefore, this work presents the implementation o...

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

PloS one
Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has ...

Experimental validation of robot-assisted cardiovascular catheterization: model-based versus model-free control.

International journal of computer assisted radiology and surgery
PURPOSE: In cardiac electrophysiology, a long and flexible catheter is delivered to a cardiac chamber for the treatment of arrhythmias. Although several robot-assisted platforms have been commercialized, the disorientation in tele-operation is still ...

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: In this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data and machine learning.

Automatic Segmentation of Acute Ischemic Stroke From DWI Using 3-D Fully Convolutional DenseNets.

IEEE transactions on medical imaging
Acute ischemic stroke is recognized as a common cerebral vascular disease in aging people. Accurate diagnosis and timely treatment can effectively improve the blood supply of the ischemic area and reduce the risk of disability or even death. Understa...

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

Medical image analysis
Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapp...

Early robot-assisted gait retraining in non-ambulatory patients with stroke: a single blind randomized controlled trial.

European journal of physical and rehabilitation medicine
BACKGROUND: Restoration of walking function is a primary concern of neurorehabilitation with respect to the aspired social and vocational reintegration. To date, the best practice for improving gait early after stroke is still object of debate. On on...

Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia.

PloS one
Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect ...