AIMC Topic: Aged, 80 and over
Clear Filters Showing 1931 to 1940 of 3475 articles
Evaluating the sit-to-stand transfer assistance from a smart walker in older adults with motor impairments.
Geriatrics & gerontology international
Jan 31, 2020
AIM: To evaluate the effectiveness and user satisfaction with the sit-to-stand (STS) assistance system of a smart walker (SW), and to identify factors associated with them in potential users.
Machine learning to predict early recurrence after oesophageal cancer surgery.
The British journal of surgery
Jan 30, 2020
BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This s...
Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.
Translational vision science & technology
Jan 29, 2020
PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images.
Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.
The Laryngoscope
Jan 28, 2020
OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identi...
Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers.
American journal of surgery
Jan 27, 2020
INTRODUCTION: In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.
Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.
Esophagus : official journal of the Japan Esophageal Society
Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Retrospective Studies
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Neural Networks, Computer
Artificial Intelligence
Outcome Assessment, Health Care
Esophageal Squamous Cell Carcinoma
Preoperative Care
Endoscopic Mucosal Resection
Sensitivity and Specificity
Neoplasm Invasiveness
Male
Area Under Curve
Middle Aged
Esophageal Neoplasms
Deep Learning
Japan
A Comparative Classification Analysis of Abdominal Aortic Aneurysms by Machine Learning Algorithms.
Annals of biomedical engineering
Jan 24, 2020
The objective of this work was to perform image-based classification of abdominal aortic aneurysms (AAA) based on their demographic, geometric, and biomechanical attributes. We retrospectively reviewed existing demographics and abdominal computed tom...
Shaping technologies for older adults with and without dementia: Reflections on ethics and preferences.
Health informatics journal
Jan 23, 2020
As a result of several years of European funding, progressive introduction of assistive technologies in our society has provided many researchers and companies with opportunities to develop new information and communication technologies aimed at over...
Observer-independent assessment of psoriasis-affected area using machine learning.
Journal of the European Academy of Dermatology and Venereology : JEADV
Jan 23, 2020
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...
Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.
International journal of radiation oncology, biology, physics
Jan 23, 2020
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...
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