The Experts below are selected from a list of 13233 Experts worldwide ranked by ideXlab platform
Maria José De Paula Castanho - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Expert System for predicting pathological stage of prostate cancer
Expert Systems with Applications, 2013Co-Authors: Maria José De Paula Castanho, Fábio Hernandes, Sandro Rautenberg, A. BillisAbstract:Prostate cancer is the second most common cancer among men, responsible for the loss of half a million lives each year worldwide, according to the World Health Organization. In prostate cancer, definitive therapy such as radical prostatectomy, is more effective when the cancer is organ-confined. The aim of this study is to investigate the performance of some Fuzzy Expert Systems in the classification of patients with confined or non-confined cancer. To deal with the intrinsic uncertainty about the variables utilized to predict cancer stage, the developed approach is based on Fuzzy Set Theory. A Fuzzy Expert System was developed with the Fuzzy rules and membership functions tuned by a genetic algorithm. As a result, the utilized approach reached better precision taking into account some correlated studies.
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Fuzzy Expert System: An example in prostate cancer
Applied Mathematics and Computation, 2008Co-Authors: Maria José De Paula Castanho, Laécio Carvalho De Barros, Akebo Yamakami, Laércio Luis VenditeAbstract:Fuzzy set theory has been applied to many fields in which uncertainty is present as, for example, in medical diagnosis. In this paper, we propose a Fuzzy Expert System as an alternative to predict pathological stage of prostate cancer. Utilizing uncertain variables and approximate reasoning we construct a Fuzzy rule-based System. Data of 190 patients submitted to radical prostatectomy were analyzed, seeking the test performance by the receiver operating characteristic (ROC) curve. The Fuzzy Expert System constructed is an additional tool to predict the pathological stage of prostate cancer and has a performance that is similar to the one presented by probability tables.
A. Billis - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Expert System for predicting pathological stage of prostate cancer
Expert Systems with Applications, 2013Co-Authors: Maria José De Paula Castanho, Fábio Hernandes, Sandro Rautenberg, A. BillisAbstract:Prostate cancer is the second most common cancer among men, responsible for the loss of half a million lives each year worldwide, according to the World Health Organization. In prostate cancer, definitive therapy such as radical prostatectomy, is more effective when the cancer is organ-confined. The aim of this study is to investigate the performance of some Fuzzy Expert Systems in the classification of patients with confined or non-confined cancer. To deal with the intrinsic uncertainty about the variables utilized to predict cancer stage, the developed approach is based on Fuzzy Set Theory. A Fuzzy Expert System was developed with the Fuzzy rules and membership functions tuned by a genetic algorithm. As a result, the utilized approach reached better precision taking into account some correlated studies.
William W. Melek - One of the best experts on this subject based on the ideXlab platform.
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A fastening tool tracking System using an IMU and a position sensor with Kalman filters and a Fuzzy Expert System
IEEE Transactions on Industrial Electronics, 2009Co-Authors: Seong Hoon Peter Won, Farid Golnaraghi, William W. MelekAbstract:This paper utilizes an intelligent System which incorporates Kalman filters (KFs) and a Fuzzy Expert System to track the tip of a fastening tool and to identify the fastened bolt. This System employs one inertial measurement unit and one position sensor to determine the orientation and the center of mass location of the tool. KFs are used to estimate the orientation of the tool and the center of mass location of the tool. Although a KF is used for the orientation estimation, orientation error increases over time due to the integration of angular velocity error. Therefore, a methodology to correct the orientation error is required when the System is used for an extended period of time. This paper proposes a method to correct the tilt angle and orientation errors using a Fuzzy Expert System. When a tool fastens a bolt, the System identifies the fastened bolt using a Fuzzy Expert System. Through this bolt identification step, the 3-D orientation error of the tool is corrected by using the location and orientation of the fastened bolt and the position sensor outputs. Using the orientation correction method will, in turn, result in improved reliability in determining the tool tip location. The fastening tool tracking System was experimentally tested in a lab environment, and the results indicate that such a System can successfully identify the fastened bolts.
Maria Doina Schipor - One of the best experts on this subject based on the ideXlab platform.
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improving computer based speech therapy using a Fuzzy Expert System
Computing and Informatics \ Computers and Artificial Intelligence, 2010Co-Authors: Ovidiu Andrei Schipor, Stefan Gheorghe Pentiuc, Maria Doina SchiporAbstract:In this paper we present our work about Computer Based Speech Therapy Systems optimization. We focus especially on using a Fuzzy Expert System in order to determine specific parameters of personalized therapy, i.e. the number, length and content of training sessions. The efficiency of this new approach was tested during an experiment performed with our CBST, named LOGOMON.
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Architecture of a Fuzzy Expert System Used for Dyslalic Children Therapy
arXiv: Artificial Intelligence, 2008Co-Authors: Ovidiu Andrei Schipor, Stefan Gheorghe Pentiuc, Maria Doina SchiporAbstract:In this paper we present architecture of a Fuzzy Expert System used for therapy of dyslalic children. With Fuzzy approach we can create a better model for speech therapist decisions. A software interface was developed for validation of the System. The main objectives of this task are: personalized therapy (the therapy must be in according with child’s problems level, context and possibilities), speech therapist assistant (the Expert System offer some suggestion regarding what exercises are better for a specific moment and from a specific child), (self) teaching (when System’s conclusion is different that speech therapist’s conclusion the last one must have the knowledge base change possibility).
Samarjit Kar - One of the best experts on this subject based on the ideXlab platform.
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hypertension diagnosis a comparative study using Fuzzy Expert System and neuro Fuzzy System
IEEE International Conference on Fuzzy Systems, 2013Co-Authors: Sujit Das, Pijush Kanti Ghosh, Samarjit KarAbstract:Hypertension is called the silent killer because it has no symptoms and can cause serious trouble if left untreated for a long time. It has a major role for stroke, heart attacks, heart failure, aneurysms of the arteries, peripheral arterial diseases, chronic kidney disease etc. An intelligent and accurate diagnostic System is mandatory for better diagnosis and treatment of hypertension patients. This study develops a Fuzzy Expert System to diagnose the hypertension risk for different patients based on a set of symptoms and rules. Next we design a neuro Fuzzy System for the same set of symptoms and rules using three different types of learning algorithms which are Levenberg-Marquardt (LM), Gradient Descent (GD) and Bayesian Resolution (BR) based learning functions. Then this paper presents a comparative study between Fuzzy Expert System (FES) and feed forward back propagation based neuro Fuzzy System (NFS) for hypertension diagnosis. This paper also presents a comparison among the learning functions (LM, GD and BR) where Levenberg-Marquardt based learning function shows its efficiency over the others. Comparison between FES and NFS shows the effectiveness of using NFS over FES. Here, the input data set has been collected from 10 patients whose ages are between 20 and 40 years, both for male and female. The input parameters taken are age, body mass index (BMI), blood pressure (BP), and heart rate. The diagnosis process, linguistic variables and their values were modeled based on Expert's knowledge and from existing database.
