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Robot-assisted therapy for upper-limb rehabilitation in subacute stroke patients: A systematic review and meta-analysis.

Brain and behavior
BACKGROUND: Stroke survivors often experience upper-limb motor deficits and achieve limited motor recovery within six months after the onset of stroke. We aimed to systematically review the effects of robot-assisted therapy (RT) in comparison to usua...

Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation.

Sensors (Basel, Switzerland)
Cardiovascular diseases (CVD) are often characterized by their multifactorial complexity. This makes remote monitoring and ambulatory cardiac rehabilitation (CR) therapy challenging. Current wearable multimodal devices enable remote monitoring. Machi...

Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Sensors (Basel, Switzerland)
Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brain diseases. However, major depressive disorder may also cause temporary deterioration of one's cognition known as pseudodementia. Differentiating a tr...

Controller synthesis and clinical exploration of wearable gyroscopic actuators to support human balance.

Scientific reports
Gyroscopic actuators are appealing for wearable applications due to their ability to provide overground balance support without obstructing the legs. Multiple wearable robots using this actuation principle have been proposed, but none has yet been ev...

Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy.

Physics in medicine and biology
Registration and fusion of magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) of the prostate can provide guidance for prostate brachytherapy. However, accurate registration remains a challenging task due to the lack of ground truth r...

New machine learning method for image-based diagnosis of COVID-19.

PloS one
COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In this paper, a ...

Robot-assisted combined pancreatectomy/hepatectomy for metastatic pancreatic acinar cell carcinoma: case report and review of the literature.

Clinical journal of gastroenterology
Acinar cell carcinoma (ACC) of the pancreas is a rare neoplasm with less aggressive behavior than ductal carcinoma. As a result, surgical resection for metastatic ACC is a therapeutic option which can result in long-term survival. There is a paucity ...

Semantic segmentation of cerebrospinal fluid and brain volume with a convolutional neural network in pediatric hydrocephalus-transfer learning from existing algorithms.

Acta neurochirurgica
BACKGROUND: For the segmentation of medical imaging data, a multitude of precise but very specific algorithms exist. In previous studies, we investigated the possibility of segmenting MRI data to determine cerebrospinal fluid and brain volume using a...

Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.

European journal of radiology
PURPOSE: Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the ...