AIMC Topic: Aged

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Bioinspired Smart Triboelectric Soft Pneumatic Actuator-Enabled Hand Rehabilitation Robot.

Advanced materials (Deerfield Beach, Fla.)
Quantitative assessment for post-stroke spasticity remains a significant challenge due to the encountered variable resistance during passive stretching, which can lead to the widely used modified Ashworth scale (MAS) for spasticity assessment dependi...

Patch-based feature mapping with generative adversarial networks for auxiliary hip fracture detection.

Computers in biology and medicine
BACKGROUND: Hip fractures are a significant public health issue, particularly among the elderly population. Pelvic radiographs (PXRs) play a crucial role in diagnosing hip fractures and are commonly used for their evaluation. Previous research has de...

Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and...

Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.

European radiology
OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagno...

Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.

NeuroImage
RATIONALE AND OBJECTIVES: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently ti...

Predicting cognitive decline from neuropsychiatric symptoms and Alzheimer's disease biomarkers: A machine learning approach to a population-based data.

Journal of Alzheimer's disease : JAD
BACKGROUND: The aim of this study was to examine the potential added value of including neuropsychiatric symptoms (NPS) in machine learning (ML) models, along with demographic features and Alzheimer's disease (AD) biomarkers, to predict decline or no...

Predictive models and determinants of mortality among T2DM patients in a tertiary hospital in Ghana, how do machine learning techniques perform?

BMC endocrine disorders
BACKGROUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) in lower and middle - income countries call for preventive public health interventions. Studies from Africa including those from Ghana, consistently reveal high T2DM-related mor...

Machine learning in the prediction of human wellbeing.

Scientific reports
Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine...

Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning.

Scientific reports
The aim of this study was to develop and validate a machine learning-based mortality risk prediction model for patients with severe community-acquired pneumonia (SCAP) in the intensive care unit (ICU). We collected data from two centers as the develo...

Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments.

Scientific reports
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate compu...