AIMC Topic: Young Adult

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UNRAQ-A Questionnaire for the Use of a Social Robot in Care for Older Persons. A Multi-Stakeholder Study and Psychometric Properties.

International journal of environmental research and public health
(1) Background: while there exist validated measures to assess the needs of older people, there are comparatively few validated tools to assess needs and requirements for the use of robots. Henceforth, the aim of the study is to present and validate ...

Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.

BMC medical imaging
BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measu...

Radiology "forensics": determination of age and sex from chest radiographs using deep learning.

Emergency radiology
PURPOSE: To develop and test the performance of deep convolutional neural networks (DCNNs) for automated classification of age and sex on chest radiographs (CXR).

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Scientific reports
Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convo...

Applying deep neural networks and inertial measurement unit in recognizing irregular walking differences in the real world.

Applied ergonomics
Falling injuries pose serious health risks to people of all ages, and knowing the extent of exposure to irregular surfaces will increase the ability to measure fall risk. Current gait analysis methods require overly complicated instrumentation and ha...

Pedestrian attribute recognition using two-branch trainable Gabor wavelets network.

PloS one
Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age...

Machine Learning Approaches to Predict Hepatotoxicity Risk in Patients Receiving Nilotinib.

Molecules (Basel, Switzerland)
Although nilotinib hepatotoxicity can cause severe clinical conditions and may alter treatment plans, risk factors affecting nilotinib-induced hepatotoxicity have not been investigated. This study aimed to elucidate the factors affecting nilotinib-i...

Geometric deep learning on brain shape predicts sex and age.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about t...

Predicting youth diabetes risk using NHANES data and machine learning.

Scientific reports
Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step ...