AIMC Topic: Aged, 80 and over

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Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BMC bioinformatics
BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more acc...

Activity-aware essential tremor evaluation using deep learning method based on acceleration data.

Parkinsonism & related disorders
BACKGROUND: Essential tremor (ET), one of the most common neurological disorders is typically evaluated with validated rating scales which only provide a subjective assessment during a clinical visit, underestimating the fluctuations tremor during di...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...

Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT data.

Medical image analysis
This paper aims to address the segmentation and classification of lytic and sclerotic metastatic lesions that are difficult to define by using spinal 3D Computed Tomography (CT) images obtained from highly pathologically affected cases. As the lesion...

An Orthopaedic Robotic-Assisted Rehabilitation Method of the Forearm in Virtual Reality Physiotherapy.

Journal of healthcare engineering
The use of robotic rehabilitation in orthopaedics has been briefly explored. Despite its possible advantages, the use of computer-assisted physiotherapy of patients with musculoskeletal injuries has received little attention. In this paper, we detail...

Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.

Sensors (Basel, Switzerland)
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for ...

A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: GI angiectasia (GIA) is the most common small-bowel (SB) vascular lesion, with an inherent risk of bleeding. SB capsule endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a comp...