Health Diagnosis Expert Advisory System on Trained Data Sets for Hyperthyroid

نویسندگان

  • V Prasad
  • T Srinivasa Rao
  • A Veera Reddy
  • B Chaitanya
  • Georg Peters
  • Richard Weber
  • Rene Nowatzke
  • Sara El-Sayed El-Metwally
  • Elsayed Radwan
  • Taher Hamza
چکیده

This paper presents a collection of 28 pristine symptoms which are used for the identification of Hyperthyroid disease which are heartwarming to humankind. Ghastly, Hyperthyroid affect people without being noticed until the end. In this Health Diagnose Expert Advisory System (HDEAS) we proposed a method for diagnosing the Hyperthyroid disease by enabling a list of symptoms that the person is likely to suffer from. Here the diagnosis is done by the method of prediction using Trained Data Sets(TDS) and the results are compared by using suitable Data Matching Systems (DMS). The TDS are provided by Intelligent System Laboratory of K. N. Toosi University of Technology, Imam Khomeini Hospital . Proceedings of this research showed that HDEAS can be used effectively. The acquainted knowledge is represented in the diagrams, charts and tables. The database consists of four wide classifications of Thyroid

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Thyroid disorder diagnosis based on Mamdani fuzzy inference system classifier

Introduction: Classification and prediction are two most important applications of statistical methods in the field of medicine. According to this note that the classical classification are provided due to the clinical symptom and  do not involve the use of specialized information and knowledge. Therefore, using a classifier that can combine all this information, is necessary. The aim of this s...

متن کامل

A Fuzzy Expert System & Neuro-Fuzzy System Using Soft Computing For Gestational Diabetes Mellitus Diagnosis

Gestational diabetes mellitus (GDM) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. One of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. This paper intends to propose an expert system in order to diagnose the risk of GDM by using FIS model. The knowl...

متن کامل

A Fuzzy Expert System & Neuro-Fuzzy System Using Soft Computing For Gestational Diabetes Mellitus Diagnosis

Gestational diabetes mellitus (GDM) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. One of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. This paper intends to propose an expert system in order to diagnose the risk of GDM by using FIS model. The knowl...

متن کامل

Type-2 Fuzzy Hybrid Expert System For Diagnosis Of Degenerative Disc Diseases

One-third of the people with an age over twenty have some signs of degenerated discs. However, in most of the patients the mere presence of degenerative discs is not a problem leading to pain, neurological compression, or other symptoms. This paper presents an interval type-2 fuzzy hybrid rule-based system to diagnose the abnormal degenerated discs where pain variables are represented by interv...

متن کامل

Designing an expert system for differential diagnosis of β-Thalassemia minor and Iron-Deficiency anemia using neural network

Introduction: Artificial neural networks are a type of systems that use very complex technologies and non-algorithmic solutions for problem solving. These characteristics make them suitable for various medical applications. This study set out to investigate the application of artificial neural networks for differential diagnosis of thalassemia minor and iron-deficiency anemia. Methods: It is...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014