Fuzzy Methods and Medical Diagnosis
نویسندگان
چکیده
This paper argues that fuzzy representations are appropriate in applications where there are major sources of imprecision and/or uncertainty. Case studies of fuzzy approaches to specific problems of medical diagnosis and classification are described in support of this argument. The case studies are in the areas of categorical consistency, diagnostic monitoring and scoring. The solutions use a variety of fuzzy methods including clustering, fuzzy set aggregation and type-2 fuzzy set modelling of linguistic approximations. It is concluded that the fuzzy approach to the development of artificial intelligence in application systems is beneficial in these contexts because of the need to focus on uncertainty as a main issue.
منابع مشابه
Diagnosis of Coronary Artery Disease using Neuro-fuzzy-based Method
Background & Aim: Coronary artery disease is one of the most common diseases in different societies. Coronary angiography is established as one of the best methods for diagnosis of this disease. Angiography is an invasive and costly method. Furthermore, it is associated with risks such as death, heart attack, and stroke. Thus, this study introduces a neuro-fuzzy-based method which can help the ...
متن کاملThyroid 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 کاملFuzzy Medical Expert Systems for Clinical Medicine Learning Through the Fuzzy Neural Network
Computer programs are playing key role in Medicine not only in Medical Information Systems but also in Medical Diagnosis and Surgery. Artificial Intelligence in Medicine particularly Expert Systems are used for diagnosis and robotics are used in surgery. The Robotics will assist the surgeon in Surgery. The Medical Expert Systems will assist the physician in Diagnosis. The information available ...
متن کاملA Novel Fuzzy-C Means Image Segmentation Model for MRI Brain Tumor Diagnosis
Accurate segmentation of brain tumor plays a key role in the diagnosis of brain tumor. Preset and precise diagnosis of Magnetic Resonance Imaging (MRI) brain tumor is enormously significant for medical analysis. During the last years many methods have been proposed. In this research, a novel fuzzy approach has been proposed to classify a given MRI brain image as normal or cancer label and the i...
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 کاملComparing diagnosis of depression in depressed patients by EEG, based on two algorithms :Artificial Nerve Networks and Neuro-Fuzy Networks
Background and aims: Depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. So, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. Use of this memory is latent in synthetic neuro-fuzzy algorithm. P...
متن کامل