AIMC Topic: Aged

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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 ...

Computed tomography super-resolution using deep convolutional neural network.

Physics in medicine and biology
The objective of this study is to develop a convolutional neural network (CNN) for computed tomography (CT) image super-resolution. The network learns an end-to-end mapping between low (thick-slice thickness) and high (thin-slice thickness) resolutio...

Classification of Computed Tomography Images in Different Slice Positions Using Deep Learning.

Journal of healthcare engineering
This study aimed at elucidating the relationship between the number of computed tomography (CT) images, including data concerning the accuracy of models and contrast enhancement for classifying the images. We enrolled 1539 patients who underwent cont...

Osteoporosis detection in panoramic radiographs using a deep convolutional neural network-based computer-assisted diagnosis system: a preliminary study.

Dento maxillo facial radiology
OBJECTIVES: To evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system in the detection of osteoporosis on panoramic radiographs, through a comparison with diagnoses made by ora...

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...

Machine learning algorithm-based risk prediction model of coronary artery disease.

Molecular biology reports
In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the burden of the disease. The database comprising demographic, conventional, folate/xenobiotic genetic ri...

A sequence-to-sequence model-based deep learning approach for recognizing activity of daily living for senior care.

Journal of biomedical informatics
Ensuring the health and safety of independent-living senior citizens is a growing societal concern. Researchers have developed sensor based systems to monitor senior citizens' Activity of Daily Living (ADL), a set of daily activities that can indicat...

Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Clinical & experimental ophthalmology
IMPORTANCE: Diagnosis codes are inadequate for accurately identifying herpes zoster (HZ) ophthalmicus (HZO). There is significant lack of population-based studies on HZO due to the high expense of manual review of medical records.

The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Journal of neuroengineering and rehabilitation
Despite upper extremity function playing a crucial role in maintaining one's independence in activities of daily living, upper extremity impairments remain one of the most prevalent post-stroke deficits. To enhance the upper extremity motor recovery ...