scholarly journals The use of expert systems on the differential diagnosis of urinary incontinence

2009 ◽  
Vol 43 (3) ◽  
pp. 704-710 ◽  
Author(s):  
Maria Helena Baena de Moraes Lopes ◽  
Heimar de Fátima Marin ◽  
Neli Regina Siqueira Ortega ◽  
Eduardo Massad
Keyword(s):  
Differential Diagnosis ◽  
Urinary Incontinence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Health Professionals ◽  
Special Equipment ◽  
Urodynamic Testing ◽  
Trained Personnel ◽  
Definition Of

The differential diagnosis of urinary incontinence classes is sometimes difficult to establish. As a rule, only the results of urodynamic testing allow an accurate diagnosis. However, this exam is not always feasible, because it requires special equipment, and also trained personnel to lead and interpret the exam. Some expert systems have been developed to assist health professionals in this field. Therefore, the aims of this paper are to present the definition of Artificial Intelligence; to explain what Expert System and System for Decision Support are and its application in the field of health and to discuss some expert systems for differential diagnosis of urinary incontinence. It is concluded that expert systems may be useful not only for teaching purposes, but also as decision support in daily clinical practice. Despite this, for several reasons, health professionals usually hesitate to use the computer expert system to support their decision making process.

scholarly journals Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System

2021 ◽  
Vol 13 (9) ◽  
pp. 4640
Author(s):  
Seung-Yeoun Choi ◽  
Sean-Hay Kim
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Data Analytics ◽  
High Performance ◽  
Problem Definition ◽  
Design Expert ◽  
Decision Support Process ◽  
High Performance Building

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.

Fundamentals of creating MIVAR expert systems

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Support Systems ◽  
Knowledge Bases ◽  
Computer Engineering

Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Mivar databases and rules

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Knowledge Bases ◽  
Data Models ◽  
Active Network ◽  
New Model

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Critical Review of Expert System Validation in Transportation

1997 ◽  
Vol 1588 (1) ◽  
pp. 104-109 ◽  
Author(s):  
Gary S. Spring
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Critical Review ◽  
Ad Hoc ◽  
Evaluation Process ◽  
Performance Levels ◽  
System Validation ◽  
Overall Evaluation ◽  
Definition Of ◽  
Made In

Expert system validation—that is, testing systems to ascertain whether they achieve acceptable performance levels—has with few exceptions been ad hoc, informal, and of dubious value. Very few efforts have been made in this regard in the transportation area. A discussion of the major issues involved in validating expert systems is provided, as is a review of the work that has been done in this area. The review includes a definition of validation within the context of the overall evaluation process, descriptions and critiques of several approaches to validation, and descriptions of guidelines that have been developed for this purpose.

Types of control structure in expert systems

1987 ◽  
Vol 2 (2) ◽  
pp. 123-135
Author(s):  
Jean-Pierre Laurent
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Control Structure ◽  
Precise Definition ◽  
Large Group ◽  
Software Packages ◽  
Definition Of ◽  
Distinct Separation

The concept of an expert system covers an increasingly large group of software packages which often have more dissimilarities than points in common. We shall not attempt to give a precise definition of an expert system here, because this might impose too restrictive a framework on the rest of our discussion. We shall simply state that, as is generally recognized, an expert system is a piece of software intended to resolve a certain category of problems, that it uses for this purpose a large quantity of knowledge specific to the field in question, and that in each expert system there is a very distinct separation between this knowledge and the procedures which make use of it.

What is a deep expert system? An analysis of the architectural requirements of second-generation expert systems

1989 ◽  
Vol 4 (3) ◽  
pp. 205-233 ◽  
Author(s):  
E. T. Keravnou ◽  
J. Washbrook
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Human Computer Interaction ◽  
Expert Systems ◽  
First Generation ◽  
Second Generation ◽  
Robust Solutions ◽  
Definition Of ◽  
Interaction Problem ◽  
Computer Interaction

AbstractFirst-generation expert systems have significant limitations, often attributed to their not being sufficiently deep. However, a generally accepted answer to “What is a deep expert system?” is still to be given. To answer this question one needs to answer “Why do first-generation systems exhibit the limitations they do?” thus identifying what is missing from first-generation systems and therefore setting the design objectives for second-generation (i.e. deep) systems. Several second-generation architectures have been proposed; inherent in each of these architectures is a definition of deepness. Some of the proposed architectures have been designed with the objective of alleviating a subset, rather than the whole set, of the first-generation limitations. Such approaches are prone to local, non-robust solutions. In this paper we analyze the limitations (under the categories: human-computer interaction, problem-solving flexibility, and extensibility) of the first-generation expert systems thus setting design goals for second-generation systems. On the basis of this analysis proposed second-generation architectures are reviewed and compared. The paper concludes by presenting requirements for a generic second-generation architecture.

scholarly journals Expert Systems In A Commercial Environment

2011 ◽  
Vol 3 (3) ◽  
pp. 97
Author(s):  
Vivek Shah
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Emerging Technology ◽  
Business Applications ◽  
Commercial Environment

One of the current terms in decision support methodologies is Artificial Intelligence (AI). The search for AI, particularly in potential business applications, targets techniques which collectively results in expert systems. The purpose of this article is to identify an expert system and explain how this rapidly emerging technology can be used in a commercial environment.

scholarly journals SISTEM PAKAR KESEHATAN PADA IBU HAMIL BERBASIS MOBILE WEBSITE

2015 ◽  
Vol 18 (3) ◽  
pp. 95
Author(s):  
Umi Setiyani ◽  
Arkhan Subari
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Maternal Health ◽  
Decision Support System ◽  
Expert Systems ◽  
Pregnant Women ◽  
Support System ◽  
Wireless Application Protocol ◽  
Health Expert ◽  
Wireless Application

Umi Setiyani, Arkhan Subari, in this paper explain that the maternal mortality rate in Indonesia is still high, every 1 hour, 2 maternal death. Lack of information about the health of pregnant women, to be one cause. By utilizing the WAP ( Wireless Application Protocol ) and expert systems can be made to maternal health expert system -based mobile website. Maternal health expert system is able to diagnose 15 to 61 illnesses symptoms often suffered by pregnant women . Diagnosis of the disease is designed using forward chaining inference engine with the aid of decision tables and decision trees . In addition the system is also able to calculate the daily calories needed by pregnant women using cooper . So with this system can help pregnant mothers to know their health condition . Keywords : expert system , Wireless Application Protocol , the health of pregnant women.ReferencesNatalia, Deasy Astrid. 2006. Pembangunan Sistem Pakar pada Perangkat Mobile dengan WML dan PHP untuk Penyakit Paru pada Anak. SurabayaBroto, Adi Sadewo.2010. Perancangan dan Impelentasi Sistem Pakar untuk Analisa Penyakit Dalam. Semarang : Unversitas Diponegoro.Giarratano, J.C & Rilley G. 1994. Expert Systems: Principles and Programming, 2sd edition. USA : PWS Publishing Co.Kusrini. 2008. Aplikasi Sistem Pakar. Yogyakarta : Penerbit Andi.Martin dan Oxman dalam Kusrini. 2006. Aplikasi Sistem Pakar. Yogyakarta : Penerbit Andi.Turban, E. 1995. Decision Support System dan Expert System. USA  :Prentice Hall International IncMulyono, Djoko. 2008. Pembangunan Sistem Pakar pada Perangkat Mobile dengan WML dan PHP untuk Menemukan Penyebab Kerusakan Mesin Isuzu Panther. Semarang : UnakiSurono, dkk.2009. Bahasa Indonesia Untuk Perguruan Tinggi. Semarang: Fasindo PressMc Leod dalam Turban,E. 1995. Decision Support System dan Expert System. USA : Prentice Hall International Inc.Turban dalam Mulyono, Djoko. 2008. Pembangunan Sistem Pakar pada Perangkat Mobile dengan WML dan PHP untuk Menemukan Penyebab Kerusakan Mesin Isuzu Panther. Semarang : UnakiWilson dalam Kusrini. 2006. Aplikasi Sistem Pakar. Yogyakarta : Penerbit Andi.Giarratano dan Rilley dalam Kusrini. 2006. Aplikasi Sistem Pakar. Yogyakarta : Penerbit Andi.Solichin,Achmad. 2013. Pemrograman Web dengan PHP dan MySQL. Jakarta: UBLJuman, Kundang K. 2009. Komunikasi Multimedia.JakartaNokia. 2002. XHTML Guidlines. Finlandia : Nokia Corporation.Priyandari. 2013. Tutorial Database II, Mengenal RDBMS MySQL, http://blog.priyandari.net/2013/tutorial-database-ii-mengenal-rdbms-mysql-1/, diiakses tanggal 15 Agustus 2013.Anonim. 2013. XHTML MP (eXtensible HyperText Markup Language Mobile Profile). http://www.developesrhome.com/, diakses tanggal 4 Juni 2013Dinkes Jateng. 2011. Profil Kesehatan Jateng 2011. Semarang : Dinkes JatengSetiawan (Ed). 1998. Ilmu Kebidanan, Penyakit Kandungan, dan Keluarga Berencana. Finlandia: Penerbit Buku Kedokteran EGCWiknjosastro, Hanifa. 2005. Ilmu Kandungan. Jakarta : Yayasan Bina Pustaka Sarwono Prawirohardjo.Saifuddin, Abdul Bari. 2006. Buku Acuan Nasional Pelayanan Kesehatan Maternal dan Neonatal. Jakarta : Yayasan Bina Pustaka Sarwono Prawirohardjo.Poedyasmoro, SKM. 2005. Buku Praktisi Ahli Gizi (Buku Kuliah Politeknik Kesehatan Malang). MalangWahyudi, doni. 2004. Data Mining Email. Bandung

scholarly journals Design and Development of a Methodology Based on Expert Systems, Applied to the Treatment of Pressure Ulcers

Diagnostics ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 614 ◽  
Author(s):  
Manuel Casal-Guisande ◽  
Alberto Comesaña-Campos ◽  
Jorge Cerqueiro-Pequeño ◽  
José-Benito Bouza-Rodríguez
Keyword(s):  
Decision Support ◽  
Expert Systems ◽  
Medical Treatment ◽  
Chronic Wounds ◽  
Pressure Ulcers ◽  
Cost Savings ◽  
The Subject ◽  
Definition Of ◽  
Remote Medicine

The medical treatment of chronic wounds, pressure ulcers in particular, burdens healthcare systems nowadays with high expenses that result mainly from their monitoring and assessment stages. Decision support systems applied within the ‘remote medicine’ framework may be of help, not only to the process of monitoring the evolution of chronic wounds under treatment, but also to facilitate the prevention and early detection of potential risk conditions in the affected patients. In this paper, the design and definition of a new decision-support methodology to be applied to the monitoring and assessment stages of the medical treatment process for pressure ulcers is proposed. Built upon the use and development of expert systems, the methodology makes it possible to generate alerts derived from the evolution of a patient’s chronic wound, by means of the interpretation and combination of data coming from both an image of the wound, and the considerations of a healthcare professional with expertise in the subject matter. Some positive results are already shown regarding the determination of the ulcer’s status in the tests that have been carried out so far. Therefore, it is considered that the proposed methodology might lead to substantial improvements regarding both the treatment’s efficiency and cost savings.

scholarly journals Rancang Bangun Sistem Pakar Diagnosa Penyakit Ayam Bangkok

2019 ◽  
Vol 5 (1) ◽  
pp. 52-61
Author(s):  
Aprih Widayanto ◽  
Joko Dwi Mulyanto ◽  
Ade Sulistyono
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Expert Knowledge ◽  
Computer Programs ◽  
Knowledge Based ◽  
Informed Decisions

Abstract: Expert System is a knowledge-based program that offers quality solutions for problems within a certain domain. The implementation of expert systems is widely used for commercial purposes, because expert systems are seen as a way to store expert knowledge in certain areas in computer programs, so that they can make informed decisions and think intelligently. Using Android-based methods, this program is expected to represent experts in diagnosing Kip-Bangkok disease. Expert Systems Applications diagnosis chicken bangkok provide maximum convenience for the owner of the chickens Bangkok, so owners do not have chicken bangkok meet with specialists in person, the owner of the chicken bangkok open the computer and use this expert system application instead of the disease in poultry media consultation of experts in chickens bangkok. The expert system is used as a decision support and is used as a tool for someone who has no information about the types of diseases and symptoms in bangkok chicken, as well as preventative advice. From this problem this disease can be known on the basis of the symptoms found in chicken in Bangkok and to prevent deaths by giving appropriate prevention advice. Keywords: Expert system, Application, Diagnosis of the Chicken Disease of Bangkok

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