AIMC Topic: Aged

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ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Computers in biology and medicine
Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of applications, such as access control and security/privacy requirements. The majority of reported investigations using the ECG biometric method are usually...

A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study.

BMC geriatrics
BACKGROUND: Stair ascent is one of the most important and challenging activities of daily living to maintain mobility and independence in elderly adults. Recently, various types of wearable walking assist robots have been developed to improve gait fu...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

Scandinavian journal of gastroenterology
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of this study was to develop a computer program that was able to differentiate neoplastic from non-neop...

Machine learning for real-time prediction of complications in critical care: a retrospective study.

The Lancet. Respiratory medicine
BACKGROUND: The large amount of clinical signals in intensive care units can easily overwhelm health-care personnel and can lead to treatment delays, suboptimal care, or clinical errors. The aim of this study was to apply deep machine learning method...

Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease...

Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.

European radiology
OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.

Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.

Radiology
Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...

Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques.

Methods of information in medicine
OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment (MCI), which may trigger AD, is essential to slow down the cognitive decline process.

Machine learning ensemble models predict total charges and drivers of cost for transsphenoidal surgery for pituitary tumor.

Journal of neurosurgery
OBJECTIVE: Efficient allocation of resources in the healthcare system enables providers to care for more and needier patients. Identifying drivers of total charges for transsphenoidal surgery (TSS) for pituitary tumors, which are poorly understood, r...