AIMC Topic: Iran

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Health-related quality of life among healthcare workers: a comparative analysis using regression, conditional tree and forests.

BMC public health
BACKGROUND: Considering the potential importance of health care workers (HCWs) in maintaining and improving the health of society, we decided to investigate the factors affecting the health-related quality of life (HRQoL) of HCWs using machine learni...

Application of machine learning for identification of key exposure predictors for heavy metal accumulation in hair of traffic police officers in Tehran.

The Science of the total environment
In order to determine variability and measure the major exposure factors affecting the levels of hazardous metals (such as Fe, Mn, Ni, Pb, As, Cr, and Cu) in the scalp hair of Tehran traffic police personnel, an advanced statistical method is used. T...

Artificial intelligence and academic writing questionnaire (AI-AWQ): development and validation among medical students' experiences using exploratory factor analysis.

BMC medical education
INTRODUCTION: This study aimed to develop and validate the Artificial Intelligence and Academic Writing Questionnaire (AI-AWQ) to assess participants' perceptions with AI. The primary focus was to explore the factors that influence attitudes toward A...

Application of generalized linear mixed effects random forest for identifying risk factors of prediabetes in Tehran Lipid and Glucose Study.

Scientific reports
Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...

Uncovering age-specific subtypes of pediatric obesity and metabolic syndrome using machine learning algorithms.

Scientific reports
Identifying new subgroups among children and adolescents with obesity and metabolic syndrome requires advanced clustering techniques capable of analyzing complex multidimensional data. This study aimed to employ machine learning methods to enhance th...

Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran.

Scientific reports
Freshwater ecosystems are increasingly imperiled by the dual pressures of biological invasions and climate change, necessitating robust predictive frameworks for effective management. This study integrates advanced ensemble machine learning (EML) wit...

Prognostic machine learning models for predicting postoperative complications following general surgery in Bandar Abbas, Iran: a study protocol.

BMJ open
INTRODUCTION: To enhance the quality of surgical care, complications need to be minimised. Consequently, comprehending the occurrence and risk elements for postoperative complications is essential. Subsequently, we will apply machine learning (ML) al...

Optimizing emergency shutdown system inspection, testing, and maintenance through the tool design and validation.

Scientific reports
Emergency Shutdown (ESD) systems serve as reliable control mechanisms within the petrochemical industry. These systems enhance safety by automatically shutting down processes during emergencies, mitigating hazards. The effectiveness of ESD systems is...

Predicting visual aesthetic preferences in Tehran city universities campuses using machine learning techniques.

Scientific reports
Visual aesthetic preferences fundamentally shape the restorative potential of university landscapes and have a significant impact on student well-being and engagement. This study developed Ensemble Learning Models to predict students' aesthetic prefe...

Association between exposure to PM and black carbon and the risk of childhood leukemia in Tehran: A case-control study with critical exposure time windows.

Environmental research
Limited research has explored the relationship between air pollutants and childhood leukemia during critical exposure periods, and no such research has been conducted in Tehran to date. This study assessed the association between exposure to fine par...