AIMC Topic: Young Adult

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Prevalence, associated factors, and machine learning-based prediction of depression, anxiety, and stress among university students: a cross-sectional study from Bangladesh.

Journal of health, population, and nutrition
BACKGROUND: Mental health challenges are a growing global public health concern, with university students at elevated risk due to academic and social pressures. Although several studies have exmanined mental health among Bangladeshi students, few hav...

Validity and reliability analysis of the Turkish life satisfaction scale developed through artificial intelligence.

BMC psychology
This study evaluates the validity and reliability of a Turkish Life Satisfaction Scale developed using artificial intelligence (ChatGPT) to explore AI's potential in creating psychometric tools. The scale was tested on three independent samples of Tu...

Statistical and machine-learning assessment of attitudinal, knowledge, and perceptual factors on diabetes awareness in Kuwait.

BMC medical informatics and decision making
OBJECTIVES: The primary objective was to identify and analyze the factors that impact diabetes awareness and perception among diabetic and non-diabetic participants. The study also sought to assess the effectiveness of current health awareness progra...

Prevalence and factors associated with HIV drug resistance among adult persons living with HIV/AIDS in nine countries of Sub-Saharan Africa using population-based HIV impact assessments: 2015-2019.

BMC public health
INTRODUCTION: HIV drug resistance (HIVDR) remains a significant challenge in sub-Saharan Africa (SSA) due to limited effective Treatment and healthcare resources vary. Using the first widely available HIVDR surveillance data in SSA, we calculated the...

Influencing factors for childbirth readiness among pregnant women based on the reciprocal determinism theory and backpropagation neural network: a cross-sectional study in China.

BMC pregnancy and childbirth
BACKGROUND: Childbirth readiness is essential for improving maternal health outcomes and reducing mortality, yet preparedness remains low among pregnant women globally. This study aims to identify key factors influencing childbirth readiness among Ch...

Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting.

BMC primary care
BACKGROUND: Establishing risk factors associated with severity and prognosis in the early stages of the disease is important to identify patients who need specialized care. Creating new clinical tools to improve health decisions and outcomes in the p...

AI-generated images of familiar faces are indistinguishable from real photographs.

Cognitive research: principles and implications
Human users are now able to generate synthetic face images with artificial intelligence (AI) tools. Although indistinguishable from real photographs, these images have tended to feature fictional identities that do not exist in the real world. As a r...

Determinants of student adoption of artificial intelligence applications in higher education.

Scientific reports
The integration of artificial intelligence (AI) into educational settings has the potential to transform learning experiences; however, its adoption among students remains impacted by various factors. The current study assesses the determinant factor...

Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis.

Scientific reports
The landscape of academic publishing has evolved dramatically, leading to a surge in publications and journals. The 'publish or perish' culture has resulted in undesirable practices, such as many researchers publishing in predatory journals due to in...

Identifying key influencers of patient satisfaction using an explainable machine learning approach.

Scientific reports
Patient satisfaction is a crucial measure of healthcare quality, influencing both health outcomes and care experiences. This study aims to identify the factors influencing patient satisfaction in healthcare facilities using machine learning algorithm...