AIMC Topic: Cross-Sectional Studies

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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) Jun 14, 2021
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...
Humans Asthma Environmental Exposure Poaceae Trees Child Air Pollutants Air Pollution Particulate Matter Cross-Sectional Studies Prevalence Deep Learning
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Prediction of absenteeism in public schools teachers with machine learning.

Revista de saude publica Jun 14, 2021
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.
Absenteeism Brazil Humans Child, Preschool Machine Learning ROC Curve Cross-Sectional Studies Schools
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The introduction of care robots as a leadership challenge in home care facilities in Finland.

Nursing open Jun 10, 2021
AIMS: This paper analyses the factors that influence home care employees' intention to introduce robots.
Finland Home Care Services Humans Aged Cross-Sectional Studies Leadership Robotics
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Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit.

ESMO open Jun 3, 2021
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. ...
Cross-Sectional Studies Male Smoking Neoplasms Smoking Cessation Humans Deep Learning Prospective Studies
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Cascaded Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation.

IEEE transactions on medical imaging Jun 1, 2021
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...
Tomography, X-Ray Computed Cross-Sectional Studies Humans Image Processing, Computer-Assisted Neural Networks, Computer Kidney
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Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network.

BMC public health May 26, 2021
BACKGROUND: Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorpora...
China Physical Examination Habits Osteoporosis Adult Cross-Sectional Studies Humans Neural Networks, Computer
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Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia May 24, 2021
Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aqueduct has been utilized for diagnosis of conditions such as normal pressure hydrocephalus (NPH). This...
Male Humans Middle Aged Neural Networks, Computer Infant Female Hydrocephalus, Normal Pressure Retrospective Studies Deep Learning Infant, Newborn Young Adult Cerebral Aqueduct Aged Adolescent Adult Aged, 80 and over Child, Preschool Cross-Sectional Studies Child Magnetic Resonance Imaging
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A deep learning-based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images.

Medical physics May 24, 2021
PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, which is recognized as accumulation of plaques in arterial wall tissues. Optical Coherence Tomography (OCT) is a light-based imaging system used in cardio...
Humans Adult Coronary Vessels Plaque, Atherosclerotic Cross-Sectional Studies Deep Learning Tomography, Optical Coherence Coronary Artery Disease
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Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study.

Radiology May 4, 2021
Background The interpretation of radiographs suffers from an ever-increasing workload in emergency and radiology departments, while missed fractures represent up to 80% of diagnostic errors in the emergency department. Purpose To assess the performan...
Radiologists Radiographic Image Interpretation, Computer-Assisted Adolescent Fractures, Bone Emergency Service, Hospital Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Physicians Cross-Sectional Studies Male Retrospective Studies Middle Aged Female Reproducibility of Results Humans Artificial Intelligence
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Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

JAMA network open May 3, 2021
IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) is limited by existing risk prediction models. Machine learning algorithms may result in superior pre...
Machine Learning Thienopyridines Retrospective Studies Clinical Decision-Making Female Aged Aged, 80 and over Young Adult Adult Predictive Value of Tests Humans Venous Thromboembolism Cross-Sectional Studies Risk Assessment Fibrinolytic Agents Antifibrinolytic Agents Male Adolescent Anticoagulants Gastrointestinal Hemorrhage Middle Aged Cohort Studies Atrial Fibrillation Myocardial Ischemia United States
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