AIMC Topic: Aged, 80 and over
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A miRNA-based epigenetic molecular clock for biological skin-age prediction.
Archives of dermatological research
Jun 1, 2024
Skin aging is one of the visible characteristics of the aging process in humans. In recent years, different biological clocks have been generated based on protein or epigenetic markers, but few have focused on biological age in the skin. Arrest the a...
Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma: a step towards virtual biopsy.
International journal of surgery (London, England)
Jun 1, 2024
OBJECTIVES: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour gra...
Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
May 31, 2024
PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs).
Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 31, 2024
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...
Can machine learning predict late seizures after intracerebral hemorrhages? Evidence from real-world data.
Epilepsy & behavior : E&B
May 30, 2024
INTRODUCTION: Intracerebral hemorrhage represents 15 % of all strokes and it is associated with a high risk of post-stroke epilepsy. However, there are no reliable methods to accurately predict those at higher risk for developing seizures despite the...
Incorporating preoperative frailty to assist in early prediction of postoperative pneumonia in elderly patients with hip fractures: an externally validated online interpretable machine learning model.
BMC geriatrics
May 30, 2024
BACKGROUND: This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians.
Evaluating the quality of home care in community health service centres: A machine learning approach.
Journal of advanced nursing
May 29, 2024
AIMS: The aim of the study is to develop a model using a machine learning approach that can effectively identify the quality of home care in communities.
Clinical evaluation of deep learning-enhanced lymphoma pet imaging with accelerated acquisition.
Journal of applied clinical medical physics
May 29, 2024
PURPOSE: This study aims to evaluate the clinical performance of a deep learning (DL)-enhanced two-fold accelerated PET imaging method in patients with lymphoma.
Image Interpretation, Computer-Assisted
Fluorodeoxyglucose F18
Signal-To-Noise Ratio
Whole Body Imaging
Deep Learning
Image Processing, Computer-Assisted
Lymphoma
Positron Emission Tomography Computed Tomography
Radiopharmaceuticals
Young Adult
Adult
Male
Middle Aged
Humans
Prognosis
Female
Aged
Aged, 80 and over
No playing around with robots? Ambivalent attitudes toward the use of Paro in elder care.
Nursing inquiry
May 29, 2024
This paper explores the ways in which health care professionals, family carers, and older persons expressed attitudes and opinions on using Paro, a social robot designed to stimulate patients with dementia. Thereafter, we critically evaluate existing...
Evaluating initial usability of a hand augmentation device across a large and diverse sample.
Science robotics
May 29, 2024
The advancement of motor augmentation and the broader domain of human-machine interaction rely on a seamless integration with users' physical and cognitive capabilities. These considerations may markedly fluctuate among individuals on the basis of th...
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