Chronic Disease Prediction by Analyzing Clinical Data

Prediction of chronic kidney disease in Isfahan with extracting association rules using data mining techniques

Background: Millions of deaths occur around the world each year due to lack of access to appropriate treatment for chronic kidney disease patients. Given the importance and mortality rate of this disease, early and low-cost prediction is very important. The researchers intend to identify chronic kidney disease through the optimal combination of techniques used in different stages of data mining...

A minimum data set for chronic venous disease

Design and implementation of an intelligent clinical decision support system for diagnosis and prediction of chronic kidney disease

Introduction: Chronic kidney disease (CKD) is one of the most important public health concerns worldwide. The steady increase in the number of people with End-stage renal disease (ESRD) needing a kidney transplant to survive and incur high costs, highlights early diagnosis and treatment of the disease. This study aimed to design a Clinical Decision Support System (CDSS) for diagnosing CKD and p...

modeling loss data by phase-type distribution

بیمه گران همیشه بابت خسارات بیمه نامه های تحت پوشش خود نگران بوده و روش هایی را جستجو می کنند که بتوانند داده های خسارات گذشته را با هدف اتخاذ یک تصمیم بهینه مدل بندی نمایند. در این پژوهش توزیع های فیزتایپ در مدل بندی داده های خسارات معرفی شده که شامل استنباط آماری مربوطه و استفاده از الگوریتم em در برآورد پارامترهای توزیع است. در پایان امکان استفاده از این توزیع در مدل بندی داده های گروه بندی ...

Adaptive Bug Prediction by Analyzing Project history

.................................................................................................................. x Acknowledgements...............................................................................................xii