AIMC Topic: Age Factors
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Children's animistic beliefs toward a humanoid robot and other objects.
Journal of experimental child psychology
May 9, 2024
This study examined children's beliefs about a humanoid robot by examining their behavioral and verbal responses. We investigated whether 3- and 5-year-old children would treat the humanoid robot gently along with other objects and tools with and wit...
Identification of sleep phenotypes in COPD using machine learning-based cluster analysis.
Respiratory medicine
May 6, 2024
BACKGROUND: Disturbed sleep in patients with COPD impact quality of life and predict adverse outcomes.
Deep Survival Analysis With Latent Clustering and Contrastive Learning.
IEEE journal of biomedical and health informatics
May 6, 2024
Survival analysis is employed to analyze the time before the event of interest occurs, which is broadly applied in many fields. The existence of censored data with incomplete supervision information about survival outcomes is one key challenge in sur...
Comparing fatal crash risk factors by age and crash type by using machine learning techniques.
PloS one
May 6, 2024
This study aims to use machine learning methods to examine the causative factors of significant crashes, focusing on accident type and driver's age. In this study, a wide-ranging data set from Jeddah city is employed to look into various factors, suc...
Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients Using Machine Learning and Immune Cell Infiltration Analysis.
Biochemical genetics
Apr 24, 2024
Elderly patients infected with severe acute respiratory syndrome coronavirus 2 are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms an...
Age and medial compartmental OA were important predictors of the lateral compartmental OA in the discoid lateral meniscus: Analysis using machine learning approach.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Apr 23, 2024
PURPOSE: The objective of this study was to develop a machine learning model that would predict lateral compartment osteoarthritis (OA) in the discoid lateral meniscus (DLM), from which to then identify factors contributing to lateral compartment OA,...
Advanced cardiac imaging, machine learning, and heart age for cardiovascular risk stratification.
The international journal of cardiovascular imaging
Apr 13, 2024
Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Apr 6, 2024
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.
Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).
Health services research
Mar 30, 2024
OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.
Correlating Age and Hematoma Volume with Extent of Midline Shift in Acute Subdural Hematoma Patients: Validation of an Artificial Intelligence Tool for Volumetric Analysis.
World neurosurgery
Mar 20, 2024
OBJECTIVE: Decision for intervention in acute subdural hematoma patients is based on a combination of clinical and radiographic factors. Age has been suggested as a factor to be strongly considered when interpreting midline shift (MLS) and hematoma v...
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