AIMC Topic: Iran
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Quality review and content analysis of liver complications mobile apps in Iran: A statistical and machine learning approach.
International journal of medical informatics
Feb 17, 2025
BACKGROUND: Liver disease accounts for 4 % of global mortality. The advent of mobile technology has introduced a novel domain in liver disease management. Identifying effective mobile apps with pertinent information on liver diseases is essential. Th...
Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Feb 15, 2025
OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...
Enhancing drought monitoring with a multivariate hydrometeorological index and machine learning-based prediction in the south of Iran.
Environmental science and pollution research international
Feb 13, 2025
Traditional drought indices, such as the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), often fail to capture the complexity of drought events, which involve multiple interacting variables. To address this gap, this study...
Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes.
Journal of health, population, and nutrition
Feb 7, 2025
BACKGROUND: Diabetes mellitus, an endocrine system disease, is a common disease involving many patients worldwide. Many studies are performed to evaluate the correlation between micronutrients/macronutrients on diabetes but few of them have a high st...
Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.
Reproductive health
Feb 3, 2025
BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive decisions. Considering the importance of fertility growth and strengthening positive fertility motivati...
Machine learning models for water safety enhancement.
Scientific reports
Jan 30, 2025
Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial radionuclides, and radiation generated by human activities. These radionuclides can infiltrate the human body through various pathways, potentially lead...
Predictive modeling of air quality in the Tehran megacity via deep learning techniques.
Scientific reports
Jan 8, 2025
Air pollution is a significant challenge in metropolitan areas, where increasing amounts of air pollutants threaten public health and environmental safety. The present study aims to forecast the concentrations of various air pollutants, including CO,...
Improving groundwater quality predictions in semi-arid regions using ensemble learning models.
Environmental science and pollution research international
Jan 4, 2025
Groundwater resources constitute one of the primary sources of freshwater in semi-arid and arid climates. Monitoring the groundwater quality is an essential component of environmental management. In this study, a comprehensive comparison was conducte...
Predicting Gestational Diabetes Mellitus in the first trimester using machine learning algorithms: a cross-sectional study at a hospital fertility health center in Iran.
BMC medical informatics and decision making
Jan 3, 2025
BACKGROUND: Gestational Diabetes Mellitus (GDM) is a common complication during pregnancy. Late diagnosis can have significant implications for both the mother and the fetus. This research aims to create an early prediction model for GDM in the first...
Psychotropic medications: a descriptive study of prescription trends in Tabriz, Iran, 2021-2022.
BMC psychiatry
Jan 3, 2025
INTRODUCTION: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced t...
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