AIMC Topic: Aged

Clear Filters Showing 6951 to 6960 of 14227 articles

Deep Learning Detection and Segmentation of Brain Arteriovenous Malformation on Magnetic Resonance Angiography.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent treatment planning. Manual segmentation is time-consuming and labor-intensive. Applying deep learning to automatically detect and segment bAVM might he...

[The Perspectives of Stakeholders on Users of Care Robotics at the Intersection of Age and Gender - Results of a Qualitative Analysis].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
Having to face the challenges posed by a shortage of skilled care workers and an increasing number of older people in need of care, policy makers and economic enterprises perceive care robotics as a promising solution. However, studies have shown tha...

Robot-assisted total remnant gastrectomy for interposed jejunal pouch dysfunction 25 years after proximal gastrectomy for gastric cancer: A case report.

Asian journal of endoscopic surgery
Proximal gastrectomy (PG) in combination with jejunal pouch interposition is a technique aimed at improving the postoperative dietary outcomes; however, some cases are reported to require surgical intervention owing to difficulty of food intake cause...

Research Participant Selection Bias in the Workshop Using Socially Assistive Robots for Older Adults and Its Effect on Population Representativeness.

International journal of environmental research and public health
Every research participant has their own personality characteristics. For example, older adults assisted by socially assistive robots (SAR) may have their own unique characteristics and may not be representative of the general population of older adu...

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.

Neuroradiology
PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can eval...

The effectiveness of a therapeutic robot, 'Paro', on behavioural and psychological symptoms, medication use, total sleep time and sociability in older adults with dementia: A systematic review and meta-analysis.

International journal of nursing studies
OBJECTIVE: To evaluate the effectiveness of a therapeutic robot, 'Paro', on anxiety, agitation, depression, apathy, medication use, total sleep time, and sociability among older adults with dementia.

Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease.

Journal of biomechanics
Markerless motion capture methods are continuously in development to target limitations encountered in marker-, sensor-, or depth-based systems. Previous evaluation of the KinaTrax markerless system was limited by differences in model definitions, ga...

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.

Frontiers in endocrinology
PURPOSE: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBM...

The effects of Robot-assisted gait training and virtual reality on balance and gait in stroke survivors: A randomized controlled trial.

Gait & posture
BACKGROUND: Stroke survivors often experience balance and gait problems, which can affect their quality of life and independence in daily living activities. Robot-assisted gait training, such as Lokomat with virtual reality, has been found to be effe...

Machine learning functional impairment classification with electronic health record data.

Journal of the American Geriatrics Society
BACKGROUND: Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provi...