AIMC Topic: Iran
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Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.
PloS one
Nov 24, 2015
Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biolog...
Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.
Waste management (New York, N.Y.)
Oct 9, 2015
Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verifi...
Fuzzy Rule-Based Classification System for Assessing Coronary Artery Disease.
Computational and mathematical methods in medicine
Sep 13, 2015
The aim of this study was to determine the accuracy of fuzzy rule-based classification that could noninvasively predict CAD based on myocardial perfusion scan test and clinical-epidemiological variables. This was a cross-sectional study in which the ...
Performance Analysis of Hospital Managers Using Fuzzy AHP and Fuzzy TOPSIS: Iranian Experience.
Global journal of health science
Jun 12, 2015
BACKGROUND AND OBJECTIVES: Hospitals are complex organizations that require strong and effective management. The success of such organizations depends on the performance of managers. This study provides a comprehensive set of indicators to assess the...
The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.
Medical decision making : an international journal of the Society for Medical Decision Making
Dec 1, 2014
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort ...
Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.
International archives of occupational and environmental health
Nov 29, 2014
PURPOSE: Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using art...
Improving human brucellosis susceptibility mapping using effective and simultaneously metaheuristic-based feature selection and hyperparameter tuning.
Acta tropica
Jul 1, 2025
Human Brucellosis, a neglected zoonotic disease, affects 1.6 to 2.1 million people globally each year. In Iran, it has become a significant health concern, with an average annual incidence rate of 19.91 cases per 100,000 people. This study aims to cr...
Sustainable water allocation under climate change: Deep learning approaches to predict drinking water shortages.
Journal of environmental management
Jun 1, 2025
Addressing sustainable urban water supply has become one of the most critical challenges for modern megacities, particularly in arid and semi-arid regions where rapid urbanization and climate change converge to exacerbate resource scarcity. Tehran, a...
Identifying the key factors of mercury exposure in residents of southwestern Iran using machine learning algorithms.
Environmental geochemistry and health
May 31, 2025
It is necessary to predict hair mercury (Hg) levels and specify the related effective factors to develop preventive strategies to reduce Hg exposure in different regions. This study is the first effort to investigate the effectiveness of eight machin...
The integrated fuzzy AHP and fuzzy logic techniques for mapping and prioritizing groundwater potential zone based on water quality.
Environmental monitoring and assessment
May 30, 2025
Groundwater, which is utilized to supply water demand in various sectors such as domestic water consumption, agriculture, and industry, could be achieved by delineating a groundwater potential zone. Although mapping groundwater potential zones has be...
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