AIMC Topic: Cross-Sectional Studies

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Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.

Sleep medicine
OBJECTIVE: This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique.

Role of Robotics and Artificial Intelligence in Oral Health and Preventive Dentistry - Knowledge, Perception and Attitude of Dentists.

Oral health & preventive dentistry
PURPOSE: To assess the knowledge, attitude and perception of dentists (dental students, dental school graduates/interns, postgraduate dentists) of the role of robotics (R) and artificial intelligence (AI) in oral health and preventive dentistry. The ...

Digitalization of waste management: Insights from German private and public waste management firms.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Policymakers, practitioners, and scholars have long-lauded digital technologies, such as smart waste containers or artificial intelligence for material recognition and robotic automation, as key enablers to more effective and efficient waste manageme...

Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.

Acta ophthalmologica
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...

Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Environmental pollution (Barking, Essex : 1987)
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...

Prediction of absenteeism in public schools teachers with machine learning.

Revista de saude publica
OBJECTIVE: To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms.

The introduction of care robots as a leadership challenge in home care facilities in Finland.

Nursing open
AIMS: This paper analyses the factors that influence home care employees' intention to introduce robots.

Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit.

ESMO open
BACKGROUND: Persistent smoking after cancer diagnosis is associated with increased overall mortality (OM) and cancer mortality (CM). According to the 2020 Surgeon General's report, smoking cessation may reduce CM but supporting evidence is not wide. ...

Cascaded Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation.

IEEE transactions on medical imaging
Kidney volume is an essential biomarker for a number of kidney disease diagnoses, for example, chronic kidney disease. Existing total kidney volume estimation methods often rely on an intermediate kidney segmentation step. On the other hand, automati...