Abbas Bahrampour
Department of Biostatistics and Epidemiology, Faculty of Health, Kerman University of Medical Sciences, Kerman, Iran
[ 1 ] - Does Tuberculosis Have a Seasonal Pattern among Migrant Population Entering Iran?
Background There are few quantitative documents about the seasonal incidence of tuberculosis (TB) among immigrant populations. Concerning the significant role of recognizing seasonal changes of TB in improving the TB control program, this study determines the trend and seasonal temporal changes of TB among immigrants entering Iran. Methods In this longitudinal study, data from the Iranian TB ...
[ 2 ] - Outcome Evaluation of Therapeutic Community Model in Iran
Background Evaluation of treatment programs in addiction field is a prerequisite to improve the quality of care. This study aimed to investigate the effectiveness of Therapeutic Community (TC) program in Iran. Methods Individuals who had voluntarily enrolled in the TC center within a period of seven years, from early 2005 to late 2011, entered the study. Those who successfully completed the 1...
[ 3 ] - Assessment of Trend and Seasonality in Road Accident Data: An Iranian Case Study
Background Road traffic accidents and their related deaths have become a major concern, particularly in developing countries. Iran has adopted a series of policies and interventions to control the high number of accidents occurring over the past few years. In this study we used a time series model to understand the trend of accidents, and ascertain the viability of applying ARIMA models on data...
[ 4 ] - Modeling Leukemia in Children Using Phase-type Distribution
Background: In this study, with the aim of modeling Leukemia in children using Phase-type distribution, three transitional phases including diagnosis, brain metastasis and testis/ovary metastasis, and one absorotion phase of recovery/death have been considered. The distribution was fitted and the probabilities of death or recovery were determined based on the independent variab...
[ 5 ] - پیش بینی بیماری‌های کبدی با استفاده از مدل مارکف پنهان
Background: The liver is the largest internal organ and the most important organ after heart and brain in the human body without which life is impossible. Diagnosis of liver disease requires a long time and sufficient expertise of the doctor. Statistical methods can be classified as an automated forecasting system and help specialists for quickly and accurately diagnose liver disease. Hidden Ma...
[ 6 ] - بررسی مقایسه‌ای شیوع دیابت و فشارخون در مناطق روستایی استان فارس با مناطق روستایی کشورهای منطقه‌ی مدیترانه‌ی شرقی
مقدمه: از آنجا که پایش و ارزشیابی وضعیت دیابت و فشارخون کمک شایانی به بهبود مراقبت‌های بالینی و ارزیابی دقیق وضعیت این بیماری‌ها در منطقه و حتی کشور و نیز مدیریت برنامه‌های پیشگیری و کنترل دیابت، فشارخون بالا و عوامل خطر آنها می‌نماید، به نظر می‌رسد پژوهش حاضر با ایجاد یک مقایسه‌ی مطلوب با وضعیت بیماری در مناطق روستایی منطقه‌ی مدیترانه‌ی شرقی نسبت به مناطق روستایی استان فارس به این مهم دست یازد...
[ 7 ] - Determining the Effective Factors on Gastric Cancer Using Frailty Model in South-East and North of Iran
Background and Purpose: Gastric cancer is the third leading cause of mortality in Iran after cardiovascular diseases and accidents. The aim of the present study was to assess survival and it’s affecting factors in gastric cancer patients through using Cox and parametric models along with frailty. Materials and Methods: In this study, the medical records of gastric cancer patients treat...
[ 8 ] - Risk Stratification of Hemodialysis Patients with Protein-Energy Wasting Using Hand Grip Strength and Malnutrition-Inflammation Score: are Two Indices Better than One?
Background: We aimed to detect whether risk stratification of hemodialysis (HD) patients with a combination of both malnutrition-inflammation score (MIS) and hand grip strength (HGS) indices identified more precisely patients at increased risk of protein-energy wasting (PEW). Methods: This was a deductive-analytical cross-sectional study. We determined the HGS...
[ 9 ] - مقایسه مدل‌های رگرسیون لجستیک با تحلیل جداسازی در پیش‌بینی دیابت نوع 2
Background and Objectives: Diabetes is a chronic and common metabolic disease which has no curative treatment. Logistic regression (LR) is a statistical model for the analysis and prediction in multivariate statistical techniques. Discriminant analysis is a method for separating observations in terms of dependent variable levels which can allocate any new observation after making discriminating...
[ 10 ] - پیش‌بینی بقای بیماران مبتلا به سرطان پستان با استفاده از دو مدل رگرسیون لجستیک و شبکه عصبی مصنوعی
Background and Objectives : recent years, considerable attention has been paid to statistical models for classification of medical data according to various diseases and their outcomes. Artificial neural networks have been successfully used for pattern recognition and prediction since they are not based on prior assumptions in clinical studies. This study compared two statistical models, arti...
[ 11 ] - The Prevalence of Metabolic Syndrome According to Different Criteria and its Associated Factors in Type 2 Diabetic Patients in Kerman, Iran
Metabolic syndrome is highly prevalent in type 2 diabetics and is a strong risk factor for cardiovascular diseases in such patients. The aim of this study was to determine the prevalence of metabolic syndrome according to the three criteria of ATPIII, IDF and the new criteria for metabolic syndrome diagnosis in Kerman, Iran.This cross-sectional study was performed on 950 diabetic type 2 patient...
[ 12 ] - The Relation between Hearing Loss and Smoking among Workers Exposed to Noise, Using Linear Mixed Models
Introduction: Noise is one of the most common and harmful physical factors in the working environment and has physical and psychological effects on individuals. In this study, the audiometry results of industrial workers were modeled and the effect of noise and other factors on hearing loss was examined. Materials and Methods: ...
[ 13 ] - Penalized Lasso Methods in Health Data: application to trauma and influenza data of Kerman
Background: Two main issues that challenge model building are number of Events Per Variable and multicollinearity among exploratory variables. Our aim is to review statistical methods that tackle these issues with emphasize on penalized Lasso regression model. The present study aimed to explain problems of traditional regressions due to small sample size and m...
[ 14 ] - Survival of Dialysis Patients Using Random Survival Forest Model in Low-Dimensional Data with Few-Events
Background:Dialysis is a process for eliminating extra uremic fluids of patients with chronic renal failure. The present study aimed to determine the variables that influence the survival of dialysis patients using random survival forest model (RSFM) in low-dimensional data with low events per variable (EPV). Methods:In this historical cohort study, infor...
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