AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Iran

Showing 121 to 130 of 192 articles

Clear Filters

Asthma-prone areas modeling using a machine learning model.

Scientific reports
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran conside...

Application of artificial neural networks to predict the COVID-19 outbreak.

Global health research and policy
BACKGROUND: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models based on artificial neural networks (ANN) to predict the COVID-19 outbreak for policy makers.

Prediction of the outlet flow temperature in a flat plate solar collector using artificial neural network.

Environmental monitoring and assessment
In the current research, the efficiency of a solar flat plate collector (SFPC) was examined experimentally, while the system was modeled with an artificial neural network (ANN) under semi-arid weather conditions of Rafsanjan, Iran. Based on the backp...

Prediction of Cranial Radiotherapy Treatment in Pediatric Acute Lymphoblastic Leukemia Patients Using Machine Learning: A Case Study at MAHAK Hospital.

Asian Pacific journal of cancer prevention : APJCP
BACKGROUND: Acute Lymphoblastic Leukemia (ALL) is the most common blood disease in children and is responsible for the most deaths amongst children. Due to major improvements in the treatment protocols in the 50-years period, the survivability of thi...

A Medical Decision Support System to Assess Risk Factors for Gastric Cancer Based on Fuzzy Cognitive Map.

Computational and mathematical methods in medicine
Gastric cancer (GC), one of the most common cancers around the world, is a multifactorial disease and there are many risk factors for this disease. Assessing the risk of GC is essential for choosing an appropriate healthcare strategy. There have been...

Accuracy, uncertainty, and interpretability assessments of ANFIS models to predict dust concentration in semi-arid regions.

Environmental science and pollution research international
Accurate prediction of the dust concentration (DC) is necessary to reduce its undesirable environmental effects in different geographical areas. Although the adaptive neuro-fuzzy inference system (ANFIS) is a powerful model for predicting dust events...

A comparison of fuzzy logic and TOPSIS methods for landfill site selection according to field visits, engineering geology approach and geotechnical experiments (case study: Rudbar County, Iran).

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
The present study evaluated and selected the best location among susceptible landfill sites in Rudbar County using 27 criteria, as the maximum effective criteria, in the decision-making process. The emergence and comparison between the two methods of...

Comparison of Support Vector Machine, Naïve Bayes and Logistic Regression for Assessing the Necessity for Coronary Angiography.

International journal of environmental research and public health
(1) Background: Coronary angiography is considered to be the most reliable method for the diagnosis of cardiovascular disease. However, angiography is an invasive procedure that carries a risk of complications; hence, it would be preferable for an ap...

Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction.

Environmental science and pollution research international
There is a need to develop an accurate and reliable model for predicting suspended sediment load (SSL) because of its complexity and difficulty in practice. This is due to the fact that sediment transportation is extremely nonlinear and is directed b...