AIMC Topic: Iran

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Psychometric evaluation of an instrument measuring artificial intelligence utilization in decision-making domains of healthcare organizations.

Scientific reports
The decision-making process in healthcare services encounters numerous challenges. Artificial intelligence (AI) has significantly contributed to enhancing healthcare decision-making. There is a lack of validated instruments available in the literatur...

Machine learning-based prediction of drinking water quality index in Western Tehran using KAN, MLP, and traditional models.

Environmental monitoring and assessment
In this study, the water quality index (WQI) was calculated using multivariate statistics, incorporating physical, chemical, and microbiological analysis of water samples taken from water supply networks in the western district of Tehran from 2021 to...

Predicting survival factor following suicide attempt in Iran: an ensemble machine learning technique.

BMC psychiatry
BACKGROUND: Suicide represents a significant challenge to public health that calls for a suitable intervention from the healthcare sector. Despite the typically low suicide rate among most Muslim nations, research indicates that there is an increase ...

Predicting nepetalactone accumulation in Nepeta persica using machine learning algorithms and geospatial analysis.

Scientific reports
Nepeta persica is a medicinal plant with significant pharmacological potential, primarily attributed to its high nepetalactone content. Understanding the environmental drivers of nepetalactone biosynthesis is essential for optimizing both cultivation...

Effectiveness of spiritual health-based interventions in improving health indicators of patients in Iran: a systematic review and meta-analysis.

BMC psychology
Spiritual health interventions have increasingly been recognized for their potential to improve general health outcomes. This study undertakes a systematic review and meta-analysis to evaluate their effectiveness on patient health in Iran. Data were ...

Boosted neural network modeling of psychological and social factors of work affecting safety performance and job satisfaction in the process industry.

BMC psychology
Psychological and social factors of work were found to influence workers' safety performance and job satisfaction. This study aimed to assess the effects of psychological and social factors of work affecting safety performance and job satisfaction of...

Optimization of spatio-temporal ozone (O) pollution modeling using an ensemble machine model learning with a swarm-based metaheuristic algorithm.

Ecotoxicology and environmental safety
The future of ozone (O) pollution presents significant environmental and public health challenges worldwide. High O levels can harm respiratory health, exacerbating conditions such as asthma and increasing the risk of cardiovascular diseases. Address...

Nurses perceptions and use of artificial intelligence in healthcare.

Scientific reports
The integration of artificial intelligence (AI) in nursing care is an important professional issue. However, few studies have investigated the knowledge, attitudes, application, and acceptance of artificial intelligence in nursing care. This study ai...

Advanced spatiotemporal downscaling of MODIS land surface temperature: utilizing Sentinel-1 and Sentinel-2 data with machine learning technique in Qazvin Province, Iran.

Environmental monitoring and assessment
This study presents a spatiotemporal downscaling framework for MODIS land surface temperature (LST) using Sentinel-1 and Sentinel-2 data with machine learning techniques on the Google Earth Engine (GEE) platform. Random Forest regression was applied ...

Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

PloS one
The increasing demand for natural medicine has increased the significance of Silybum marianum as a valuable medicinal plant. It is used to restore liver cells; reduce blood cholesterol; prevent prostate, skin, and breast cancer; and protect cervical ...