AIMC Topic: Iran
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The effect of climate change on cholera disease: The road ahead using artificial neural network.
PloS one
Nov 6, 2019
Climate change has been described to raise outbreaks of water-born infectious diseases and increases public health concerns. This study aimed at finding out these impacts on cholera infections by using Artificial Neural Networks (ANNs) from 2021 to 2...
Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method.
BMC medical informatics and decision making
Sep 6, 2019
BACKGROUND: Kidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the medical aspects. Leading countries in this field use a point scoring system to allocate kidneys. Hence...
A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.
Zoonoses and public health
Jul 15, 2019
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...
Determination of the physical domain for air quality monitoring stations using the ANP-OWA method in GIS.
Environmental monitoring and assessment
Jun 28, 2019
Air pollution is a major concern in some megacities of Iran. Specific cities in the country have reached an extremely harmful level of air pollution which poses a serious risk to the daily lives of Iranians. According to news reports, the air quality...
Climate data clustering effects on arid and semi-arid rainfed wheat yield: a comparison of artificial intelligence and K-means approaches.
International journal of biometeorology
May 22, 2019
Clustering algorithms are critical data mining techniques used to analyze a wide range of data. This study compares the utility of ant colony optimization (ACO), genetic algorithm (GA), and K-means methods to cluster climatic variables affecting the ...
Prediction of the five-day biochemical oxygen demand and chemical oxygen demand in natural streams using machine learning methods.
Environmental monitoring and assessment
May 19, 2019
Rivers, as the most prominent component of water resources, have a key role to play in increasing the life expectancy of living creatures. The essential characteristics of water pollutants can be described by water quality indices (WQIs). Hence, a fe...
Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability.
Journal of environmental management
May 16, 2019
In the terrestrial ecosystems, perennial challenges of increased frequency and intensity of wildfires are exacerbated by climate change and unplanned human activities. Development of robust management and suppression plans requires accurate estimates...
Predictive risk mapping of human leptospirosis using support vector machine classification and multilayer perceptron neural network.
Geospatial health
May 14, 2019
Leptospirosis is a zoonotic disease found wherever human is in direct or indirect contact with contaminated water and environment. Considering the increasing number of cases of this disease in the northern part of Iran, identifying areas characterize...
An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.
Journal of medical systems
Apr 26, 2019
Approximately 300 million people are afflicted with asthma around the world, with the estimated death rate of 250,000 cases, indicating the significance of this disease. If not treated, it can turn into a serious public health problem. The best metho...
Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.
Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation
Apr 9, 2019
OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for patient survival after transplant can help transplant centers make better decisions.
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