AIMC Topic: Feasibility Studies
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Exploiting telerobotics for sensorimotor rehabilitation: a locomotor embodiment.
Journal of neuroengineering and rehabilitation
Apr 21, 2021
BACKGROUND: Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and jud...
Robot-assisted anorectal pull-through for anorectal malformations with rectourethral and rectovesical fistula: feasibility and short-term outcome.
Surgical endoscopy
Apr 20, 2021
BACKGROUND: Multiple structures in the anorectal area are closely related to defecation, voiding and sexual function. Although laparoscopic-assisted anorectal pull-through is widely accepted as a minimally invasive surgical technique, controversy sti...
Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.
Physics in medicine and biology
Apr 16, 2021
Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studies have reported large HCC detections using automatic algorithms, but there is a lack of research on automatic detection of small HCCs (sHCCs). This st...
Feasibility and preliminary efficacy of a combined virtual reality, robotics and electrical stimulation intervention in upper extremity stroke rehabilitation.
Journal of neuroengineering and rehabilitation
Apr 14, 2021
BACKGROUND: Approximately 80% of individuals with chronic stroke present with long lasting upper extremity (UE) impairments. We designed the perSonalized UPper Extremity Rehabilitation (SUPER) intervention, which combines robotics, virtual reality ac...
Quantitative salivary gland SPECT/CT using deep convolutional neural networks.
Scientific reports
Apr 9, 2021
Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m pertechnetate aids in evaluating salivary gland function. However, gland segmentation and quantitation of gland uptake is challenging. We develop a sa...
Thyroid Neoplasms
Image Processing, Computer-Assisted
Feasibility Studies
Radiopharmaceuticals
Male
Middle Aged
Deep Learning
Salivary Gland Neoplasms
Sodium Pertechnetate Tc 99m
Parotid Gland
Single Photon Emission Computed Tomography Computed Tomography
Salivary Gland Calculi
Humans
Neural Networks, Computer
Female
Aged
Adult
Real-time coronary artery stenosis detection based on modern neural networks.
Scientific reports
Apr 7, 2021
Invasive coronary angiography remains the gold standard for diagnosing coronary artery disease, which may be complicated by both, patient-specific anatomy and image quality. Deep learning techniques aimed at detecting coronary artery stenoses may fac...
Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid-structure interaction models and machine learning methods with patient follow-up data: a feasibility study.
Biomedical engineering online
Apr 6, 2021
BACKGROUND: Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuraci...
Development and feasibility of a soft pneumatic-robotic glove to assist impaired hand function in quadriplegia patients: A pilot study.
Journal of bodywork and movement therapies
Apr 2, 2021
One of the common disorders in people with quadriplegia is having a weak grip strength that can affect activities of daily living (ADL). This study presents the design of a soft robotic glove via pneumatic actuators and feasibility according to a ran...
Deep learning and ensemble stacking technique for differentiating polypoidal choroidal vasculopathy from neovascular age-related macular degeneration.
Scientific reports
Mar 30, 2021
Polypoidal choroidal vasculopathy (PCV) and neovascular age-related macular degeneration (nAMD) share some similarity in clinical imaging manifestations. However, their disease entity and treatment strategy as well as visual outcomes are very differe...
Machine Learning Approaches to Determine Feature Importance for Predicting Infant Autopsy Outcome.
Pediatric and developmental pathology : the official journal of the Society for Pediatric Pathology and the Paediatric Pathology Society
Mar 30, 2021
INTRODUCTION: Sudden unexpected death in infancy (SUDI) represents the commonest presentation of postneonatal death. We explored whether machine learning could be used to derive data driven insights for prediction of infant autopsy outcome.
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