AIMC Topic: Aged

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Machine learning models for screening carotid atherosclerosis in asymptomatic adults.

Scientific reports
Carotid atherosclerosis (CAS) is a risk factor for cardiovascular and cerebrovascular events, but duplex ultrasonography isn't recommended in routine screening for asymptomatic populations according to medical guidelines. We aim to develop machine le...

Design and Simulation Analysis of a Robot-Assisted Gait Trainer with the PBWS System.

Journal of healthcare engineering
In response to the ever-increasing demand of lower limb rehabilitation, this paper presents a novel robot-assisted gait trainer (RGT) to assist the elderly and the pediatric patients with neurological impairments in the lower limb rehabilitation trai...

Efficacy and Safety of Appropriate Shocks and Antitachycardia Pacing in Transvenous and Subcutaneous Implantable Defibrillators: Analysis of All Appropriate Therapy in the PRAETORIAN Trial.

Circulation
BACKGROUND: The PRAETORIAN trial (A Prospective, Randomized Comparison of Subcutaneous and Transvenous Implantable Cardioverter Defibrillator Therapy) showed noninferiority of subcutaneous implantable cardioverter defibrillator (S-ICD) compared with ...

Fully automated deep learning for knee alignment assessment in lower extremity radiographs: a cross-sectional diagnostic study.

Skeletal radiology
OBJECTIVES: Accurate assessment of knee alignment and leg length discrepancy is currently measured manually from standing long-leg radiographs (LLR), a process that is both time consuming and poorly reproducible. The aim was to assess the performance...

Development and validation of the 3D U-Net algorithm for segmentation of pelvic lymph nodes on diffusion-weighted images.

BMC medical imaging
BACKGROUND: The 3D U-Net model has been proved to perform well in the automatic organ segmentation. The aim of this study is to evaluate the feasibility of the 3D U-Net algorithm for the automated detection and segmentation of lymph nodes (LNs) on pe...

Deep-learning image-reconstruction algorithm for dual-energy CT angiography with reduced iodine dose: preliminary results.

Clinical radiology
AIM: To evaluate the computed tomography (CT) attenuation values, background noise, arterial depiction, and image quality in whole-body dual-energy CT angiography (DECTA) at 40 keV with a reduced iodine dose using deep-learning image reconstruction (...

A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.

Sensors (Basel, Switzerland)
Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laborator...

Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans.

Communications biology
Deep learning (DL) is a breakthrough technology for medical imaging with high sample size requirements and interpretability issues. Using a pretrained DL model through a radiomics-guided approach, we propose a methodology for stratifying the prognosi...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Nutrients
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...

Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 41...