AIMC Topic: Iran

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Tecomella undulata under threat: The impact of climate change on the distribution of a valuable tree species using a machine learning model.

PloS one
Climate change has emerged as a significant driver of biodiversity loss, with profound implications for species distribution. This study assessed the current and future distribution of Tecomella undulata (Desert teak), an economically and medicinally...

Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data.

PloS one
BACKGROUND: Road traffic accidents (RTAs) are a major public health concern with significant health and economic burdens. Identifying high-risk areas and key contributing factors is essential for developing targeted interventions. While machine learn...

Harnessing deep learning for fusion-based heavy metal contamination index prediction in groundwater.

Journal of contaminant hydrology
Groundwater contamination by heavy metals presents a major environmental threat with serious implications for public health and resource sustainability. This study proposes a novel deep learning-based data fusion framework to predict heavy metal cont...

Readiness to use artificial intelligence: a comparative study among dental faculty members and students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is prone to become a key element in dentistry, especially education and practice. Understanding the dental students' perspectives, who will be the next generation of practitioners, is crucial for effective tec...

Development of a machine learning model to identify the predictors of the neonatal intensive care unit admission.

Scientific reports
Scientists aim to create a system that can predict the likelihood of newborns being admitted to the neonatal intensive care unit (NICU) by combining various statistical methods. This prediction could potentially reduce the negative health outcomes, d...

Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.

Scientific reports
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...

Managers' perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings.

International journal of medical informatics
BACKGROUND: Over the past decade, artificial intelligence (AI) has transformed healthcare systems by improving cost control, clinical decision-making, and chronic disease management. This study assessed healthcare managers' perceptions of AI use in h...

Psychological hardiness, sleepiness, and fatigue as predictors of occupational errors in nurses: implications for enhancing nurse well-being and patient safety.

Industrial health
Nurses are at increased risk of making professional errors due to a combination of interrelated factors. We investigated the effects of sleepiness, fatigue, psychological hardiness, and demographic factors on the frequency of medical errors among act...

A novel approach for calculating food safety models and health risk assessments of potentially toxic elements (PTEs) in cow milk.

Food chemistry
This study introduces the Milk Quality Index (MQI), a novel metric for assessing milk quality that utilizes machine learning to enhance predictive accuracy. Lead (Pb) levels (318 ± 185 mg/kg) exceeded safety limits, with chromium (Cr), aluminum (Al),...

Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.

BMC gastroenterology
BACKGROUND AND AIM: Colorectal cancer is among the most prevalent and deadliest cancers. Early prediction of metastasis in patients with colorectal cancer is crucial in preventing it from the advanced stages and enhancing the prognosis among these pa...