AIMC Topic: Latent Class Analysis

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Ethical compliance and institutional policy support for artificial intelligence integration in African TVET Education: A structural equation modeling approach.

PloS one
As artificial intelligence (AI) reshapes educational landscapes, ensuring ethical alignment and institutional responsiveness is essential particularly in skill-intensive sectors such as Technical and Vocational Education and Training (TVET). In this ...

Modeling older adults' continuance intention toward mobile health apps: a dual-path SEM-ANN approach.

BMC public health
BACKGROUND: With the rapid growth of the aging population, older adults in China face significant challenges in health management, and their continuance intention to use mobile health applications remains lower than that of younger users.

Influence of leadership on the adoption of circular and digital business models using PLS-SEM analysis.

Scientific reports
In a business environment characterised by growing pressure towards sustainability and digital transformation, leadership emerges as a determining factor in the adoption of sustainable, technology-driven business models. This study analyses how leade...

Classifying complex multimorbidity using latent class analysis and machine learning to generate insights into clustering of mental and cardiometabolic conditions.

PloS one
Machine learning techniques earn higher accuracy and robustness in multimorbidity prediction at this moment in time. Among various forms of multimorbidity, complex multimorbidity, especially the intersection of cardiometabolic disorders and mental he...

Identifying subtypes of functional dentition in older adults: a population-based regression and latent class analysis.

Clinical oral investigations
OBJECTIVES: This study aimed to explore the latent factors associated to functional dentition (FD), quantify their clustering across probability levels, and derive precision prevention strategies.

Predictive modeling of adaptive behavior trajectories in autism: insights from a clinical cohort study.

Translational psychiatry
Research aimed at understanding how baseline clinical and demographic characteristics influence outcomes over time is critically important to inform individualized therapeutic programs for children with neurodevelopmental differences. This study char...

Predicting art university students' entrepreneurial intention: A hybrid SEM-ANN approach.

PloS one
In recent years, academics and policymakers have increasingly focused on entrepreneurial behavior among university students. While existing studies have explored the entrepreneurial intention (EI) of students from various academic disciplines, few ha...

Factors influencing adoption intentions to use AIGC for health information: findings from SEM and fsQCA.

Frontiers in public health
BACKGROUND: With the rapid advancement of artificial intelligence technologies, AI-generated content (AIGC) was increasingly applied in the health information sector, becoming a vital tool to enhance the efficiency and quality of health information e...

SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

BMC medical informatics and decision making
AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) devices for diabetic retinopathy screening and the related influencing factors.

LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data.

Proceedings of the National Academy of Sciences of the United States of America
Disease and behavior subtype identification is of significant interest in biomedical research. However, in many settings, subtype discovery is limited by a lack of robust statistical clustering methods appropriate for binary data. Here, we introduce ...