AIMC Topic: Iran
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Prognostic Features for Overall Survival in Male Diabetic Patients Undergoing Hemodialysis Using Elastic Net Penalized Cox Regression; A Machine Learning Approach.
Archives of Iranian medicine
Jan 1, 2025
BACKGROUND: Diabetics constitute a significant percentage of hemodialysis (HD) patients with higher mortality, especially among male patients. A machine learning algorithm was used to optimize the prediction of time to death in male diabetic hemodial...
Different pixel sizes of topographic data for prediction of soil salinity.
PloS one
Dec 31, 2024
Modeling techniques can be powerful predictors of soil salinity across various scales, ranging from local landscapes to global territories. This study was aimed to examine the accuracy of soil salinity prediction model integrating ANNs (artificial ne...
Web application using machine learning to predict cardiovascular disease and hypertension in mine workers.
Scientific reports
Dec 30, 2024
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 201...
Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.
Scientific reports
Dec 28, 2024
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and miti...
Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression.
Journal of research in health sciences
Dec 25, 2024
BACKGROUND: Breast cancer (BC) is the most common cancer in women, and it is important to identify models that can accurately predict mortality in patients with this cancer. The aim of the present study was to use the elastic net regression and artif...
Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.
BMC cardiovascular disorders
Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
Unravelling intubation challenges: a machine learning approach incorporating multiple predictive parameters.
BMC anesthesiology
Dec 18, 2024
BACKGROUND: To protect patients during anesthesia, difficult airway management is a serious issue that needs to be carefully planned for and carried out. Machine learning prediction tools have recently become increasingly common in medicine, frequent...
Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran.
Environmental science and pollution research international
Dec 14, 2024
This study aimed to integrate game theory and deep learning algorithms with the InVEST Ecosystem Services Model (IESM) for Sediment Retention (SR) modeling in the Kasilian watershed, Iran. The Kasilian watershed is characterized by multiple sub-water...
Enhancing groundwater quality prediction through ensemble machine learning techniques.
Environmental monitoring and assessment
Dec 4, 2024
Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensembl...
Application of machine learning in breast cancer survival prediction using a multimethod approach.
Scientific reports
Dec 3, 2024
Breast cancer is one of the most prevalent cancers with an increasing trend in both incidence and mortality rates in Iran. Survival analysis is a pivotal measure in setting appropriate care plans. To the best of our knowledge, this study is pioneeri...
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