AIMC Topic: Iran
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Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.
Scientific reports
Jul 1, 2025
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...
Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.
BMC gastroenterology
Apr 18, 2025
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...
Prediction of barberry witches' broom rust disease using artificial intelligence models: a case study in South Khorasan, Iran.
Scientific reports
Apr 16, 2025
The South Khorasan Province in Iran is the main producer of seedless barberry, accounting for 98% of the country's production. This has led to significant economic growth in the region. However, the cultivation of barberry is threatened by the rust f...
Artificial Intelligence (AI) and the future of Iran's Primary Health Care (PHC) system.
BMC primary care
Mar 21, 2025
OBJECTIVE: The rapid adoption of Artificial Intelligence (AI) in health service delivery underscores the need for awareness, preparedness, and strategic utilization of AI's potential to optimize Primary Health Care (PHC) systems. This study aims to e...
Enhancement of standardized precipitation evapotranspiration index predictions by machine learning based on regression and soft computing for Iran's arid and hyper-arid region.
PloS one
Mar 18, 2025
Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, ...
Presenting a prediction model for HELLP syndrome through data mining.
BMC medical informatics and decision making
Mar 17, 2025
BACKGROUND: The HELLP syndrome represents three complications: hemolysis, elevated liver enzymes, and low platelet count. Since the causes and pathogenesis of HELLP syndrome are not yet fully known and well understood, distinguishing it from other pr...
Liver margin segmentation in abdominal CT images using U-Net and Detectron2: annotated dataset for deep learning models.
Scientific reports
Mar 13, 2025
The segmentation of liver margins in computed tomography (CT) images presents significant challenges due to the complex anatomical variability of the liver, with critical implications for medical diagnostics and treatment planning. In this study, we ...
Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses.
BMC medical informatics and decision making
Mar 6, 2025
INTRODUCTION: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dysfunction and the development ...
Advanced deep learning models for predicting elemental concentrations in iron ore mine using XRF data: a cost-effective alternative to ICP-MS methods.
Environmental geochemistry and health
Mar 5, 2025
Accurate elemental analysis is a critical requirement for mineral exploration, particularly in regions like Iran, where the mining sector has experienced a substantial increase in exploration activities over the past decade. Inductively Coupled Plasm...
Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward.
BMC medical education
Feb 18, 2025
BACKGROUND: Measuring artificial intelligence (AI) readiness among medical students is essential to assess how prepared future doctors are to work with AI technology. Therefore, this study aimed to examine the factors influencing AI readiness among m...
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