Diagnosis of the diseases--using a GA-fuzzy approach
نویسندگان
چکیده
The objective of our study is to design an expert system by modelling the knowledge and thinking process of a doctor. A fuzzy logic controller (FLC) is used to model the process and a genetic algorithm (GA) helps to select a number of good rules from a manually constructed large rule base of an FLC, based on the opinion of 10 doctors. The GA-based tuning is done off-line. Once the optimized rule base of the FLC is obtained, it can diagnose the disease, on-line. The scope of the present work has been extended to two diseases, namely Pneumonia and Jaundice. The symptoms of each disease are fed as inputs to the FLC and the output, i.e., grade of a disease is determined. 2004 Elsevier Inc. All rights reserved.
منابع مشابه
A Fuzzy-GA Approach for Parameter Optimization of A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children
Hybrid fuzzy expert systems are one of the most practical intelligent paradigm of soft computing techniques with the high potential for managing uncertainty associated to the medical diagnosis. The potential of genetic algorithm (GA) by inspiring from natural evolution as a learning and optimization technique has been vastly concentrated for improving fuzzy expert systems. In this paper, the GA...
متن کاملType-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 کاملDIAGNOSIS OF BREAST LESIONS USING THE LOCAL CHAN-VESE MODEL, HIERARCHICAL FUZZY PARTITIONING AND FUZZY DECISION TREE INDUCTION
Breast cancer is one of the leading causes of death among women. Mammography remains today the best technology to detect breast cancer, early and efficiently, to distinguish between benign and malignant diseases. Several techniques in image processing and analysis have been developed to address this problem. In this paper, we propose a new solution to the problem of computer aided detection and...
متن کاملUNCERTAINTY ANALYSIS OF STABILITY OF GRAVITY DAMS USING THE FUZZY SET THEORY
This paper introduces a methodology for considering the uncertainties in stability analysis of gravity dams. For this purpose, a conceptual model based on the fuzzy set theory and Genetic Algorithm (GA) optimization is developed to be coupled to a gravity dam analysis model. The uncertainties are represented by the fuzzy numbers and the GA is used to estimate in what...
متن کاملDecision making in medical investigations using new divergence measures for intuitionistic fuzzy sets
In recent times, intuitionistic fuzzy sets introduced by Atanassov has been one of the most powerful and flexible approaches for dealing with complex and uncertain situations of real world. In particular, the concept of divergence between intuitionistic fuzzy sets is important since it has applications in various areas such as image segmentation, decision making, medical diagnosis, pattern reco...
متن کاملDesigning a Combined-fuzzy Methodology to Improve Organizational Diagnosis Process Effectiveness through Identification and Assessment of Effective Parameters
Organizational diagnosis is a systematic and scientific method to identify, categorize and single out the obstacles and their impact on organizational performance through interaction between internal and external views and preparation and setting up operational plans to solve them in the organization. Providing standard products and emphasizing on the financial measures do not guarantee the sur...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Inf. Sci.
دوره 162 شماره
صفحات -
تاریخ انتشار 2004