AIMC Topic: Age Factors
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Exploring Shared and Unique Predictors of Positive and Negative Risk-Taking Behaviors Among Chinese Adolescents Through Machine-Learning Approaches: Discovering Gender and Age Variations.
Journal of youth and adolescence
Dec 11, 2024
Despite extensive research on the impact of individual and environmental factors on negative risk-taking behaviors, the understanding of these factors' influence on positive risk-taking, and how it compares to negative risk taking, remains limited. T...
Differential impact of CD34+ cell dose for different age groups in allogeneic hematopoietic cell transplantation for acute leukemia: a machine learning-based discovery.
Experimental hematology
Nov 23, 2024
Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk fa...
Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach.
PloS one
Nov 22, 2024
This study aimed to develop image-analysis-based classification models for distinguishing individuals younger and older than 30 using the medial clavicle. We extracted 2D images of the medial clavicle from multi-slice computed tomography (MSCT) scans...
Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.
Cardiovascular diabetology
Nov 15, 2024
BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop ...
Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.
CPT: pharmacometrics & systems pharmacology
Nov 14, 2024
Age and aging are important predictors of health status, disease progression, drug kinetics, and effects. The purpose was to develop ensemble learning-based physiological age (PA) models for evaluating drug metabolism. National Health and Nutrition E...
Predicting stroke severity of patients using interpretable machine learning algorithms.
European journal of medical research
Nov 14, 2024
BACKGROUND: Stroke is a significant global health concern, ranking as the second leading cause of death and placing a substantial financial burden on healthcare systems, particularly in low- and middle-income countries. Timely evaluation of stroke se...
Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.
European respiratory review : an official journal of the European Respiratory Society
Nov 13, 2024
BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.
Representation of intensivists' race/ethnicity, sex, and age by artificial intelligence: a cross-sectional study of two text-to-image models.
Critical care (London, England)
Nov 11, 2024
BACKGROUND: Integrating artificial intelligence (AI) into intensive care practices can enhance patient care by providing real-time predictions and aiding clinical decisions. However, biases in AI models can undermine diversity, equity, and inclusion ...
Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.
Scientific reports
Nov 6, 2024
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...
The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study.
International journal of surgery (London, England)
Nov 1, 2024
BACKGROUND: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed t...
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