scholarly journals A generic expert system framework with fuzzy Bayesian inference for medical classification and diagnosis in cardialogy [i.e. cardiology

2021 ◽  
Author(s):  
Hossein Rahnama
Keyword(s):  
General Practitioner ◽  
Expert System ◽  
Medical Knowledge ◽  
Decision Support Model ◽  
Diagnostic Decision ◽  
Suitable Treatment ◽  
Patient’S Information ◽  
Communications Protocol ◽  
Medical Records System ◽  
Rule Bases

Medical knowledge is expanding fast and it is difficult for general practitioners to remain abreast of all medical domains. Also, access to domain specialist is limited due to availability and geographical constraints. In many situations the diagnosis in [sic] upon the decision of the general practitioner and in cases this has resulted in the problem of patient's misdiagnosis. The purpose of this research is to create an expert system as a decision support model which is capable of risk analysis for diagnosis based on the patient's demography and laboratory tests. The expert system is designed in compliancy with medical communications protocol such as HL7 and can be integrated to any HL7 compliant Electronic Medical records system to provide more intelligence in diagnosis. Using linear scoring models and Fuzzy logic, the patient's demography and laboratory results will be used as rule bases. Such knowledge will be used as priors for a Bayesian engine to create the diagnostic spaces. Patient's information is compared in the space and the general practitioner can select between the possible hypotheses. Each diagnostic decision will be associated with a risk value. Using such scoring model provides a new semantic in diagnosis by providing risk values for every diagnosis made and by suggesting the most suitable treatment. Unlike many other existing expert systems, the architecture is designed in a generic standard which provides the capability to use the system for all medical domains. Achieving this generality has been a major goal achieved and its details are discussed in this document.

scholarly journals A generic expert system framework with fuzzy Bayesian inference for medical classification and diagnosis in cardialogy [i.e. cardiology

2021 ◽  
Author(s):  
Hossein Rahnama
Keyword(s):  
General Practitioner ◽  
Expert System ◽  
Medical Knowledge ◽  
Decision Support Model ◽  
Diagnostic Decision ◽  
Suitable Treatment ◽  
Patient’S Information ◽  
Communications Protocol ◽  
Medical Records System ◽  
Rule Bases

Medical knowledge is expanding fast and it is difficult for general practitioners to remain abreast of all medical domains. Also, access to domain specialist is limited due to availability and geographical constraints. In many situations the diagnosis in [sic] upon the decision of the general practitioner and in cases this has resulted in the problem of patient's misdiagnosis. The purpose of this research is to create an expert system as a decision support model which is capable of risk analysis for diagnosis based on the patient's demography and laboratory tests. The expert system is designed in compliancy with medical communications protocol such as HL7 and can be integrated to any HL7 compliant Electronic Medical records system to provide more intelligence in diagnosis. Using linear scoring models and Fuzzy logic, the patient's demography and laboratory results will be used as rule bases. Such knowledge will be used as priors for a Bayesian engine to create the diagnostic spaces. Patient's information is compared in the space and the general practitioner can select between the possible hypotheses. Each diagnostic decision will be associated with a risk value. Using such scoring model provides a new semantic in diagnosis by providing risk values for every diagnosis made and by suggesting the most suitable treatment. Unlike many other existing expert systems, the architecture is designed in a generic standard which provides the capability to use the system for all medical domains. Achieving this generality has been a major goal achieved and its details are discussed in this document.

MEDUSA: A Fuzzy Expert System for Medical Diagnosis of Acute Abdominal Pain

1994 ◽  
Vol 33 (05) ◽  
pp. 522-529 ◽  
Author(s):  
M. Fathi-Torbaghan ◽  
D. Meyer
Keyword(s):  
Fuzzy Logic ◽  
Abdominal Pain ◽  
Expert System ◽  
Acute Abdominal Pain ◽  
Medical Knowledge ◽  
Clinical Problem ◽  
Fuzzy Relations ◽  
Diagnostic Decision ◽  
Special Cases ◽  
Hybrid Concept

Abstract:Even today, the diagnosis of acute abdominal pain represents a serious clinical problem. The medical knowledge in this field is characterized by uncertainty, imprecision and vagueness. This situation lends itself especially to be solved by the application of fuzzy logic. A fuzzy logic-based expert system for diagnostic decision support is presented (MEDUSA). The representation and application of uncertain and imprecise knowledge is realized by fuzzy sets and fuzzy relations. The hybrid concept of the system enables the integration of rulebased, heuristic and casebased reasoning on the basis of imprecise information. The central idea of the integration is to use casebased reasoning for the management of special cases, and rulebased reasoning for the representation of normal cases. The heuristic principle is ideally suited for making uncertain, hypothetical inferences on the basis of fuzzy data and fuzzy relations.

A Knowledge-Based Approach to Design Partial Journal Bearings

1994 ◽  
Author(s):  
M. Affan Badar ◽  
Rao R. Guntur
Keyword(s):  
Expert System ◽  
Design Procedure ◽  
Maximum Load ◽  
Journal Bearings ◽  
Decision Criteria ◽  
Utility Value ◽  
Knowledge Based ◽  
Bearing Design ◽  
Design Solutions ◽  
Rule Bases

Abstract Various methods for designing hydrodynamic partial journal bearings are reviewed and an integrated and dependable design procedure is (developed. Knowledge and rule bases pertaining to the design of journal bearings having arcs of 180°, 120°. and 60° are either gathered or derived and represented properly. An expert system is developed using the databases and rulebases. The bearing design is based on one of the following decision criteria: the maximum load, the minimum friction, or the optimal clearance The expert system makes an exhaustive search for all the design solutions. Utility value of each of the final solutions is calculated and the design solutions having utility values above a certain limit are stored The results are presented to demonstrate the usefulness of the knowledge-based approach.

scholarly journals Modularized Cutting Tool Selection Expert System

2014 ◽  
Vol 8 (1) ◽  
pp. 892-898
Author(s):  
Chen Wang ◽  
Wu Zhao ◽  
Ling Chen ◽  
Kai Zhang ◽  
Xin Guo
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Feature Recognition ◽  
Cutting Tool ◽  
Tool Material ◽  
Tool Selection ◽  
Type Calculation ◽  
Rule Bases ◽  
Cutting Problem ◽  
Selection Of

This paper is to present a rule-based cutting tool selecting expert system which has knowledge modules and rule bases. Besides, according to different process targets, the selection progress will apply corresponding constraints and rule modules. The logic of tool selection follows a decision-making procedure as an experienced engineers. The strategy of system is to guide the user through several standard steps: information input; feature recognition; selection of machining method; selection of tool material and type; calculation of process parameter and solving cutting problem. This system also has a modularized structure which allows adding new functions and new modules to expand knowledge base and data base. Modules involves in this system are composed of the user interface, knowledge acquisition facility, explanation facility, the knowledge base module, the inference engine and the database module.

Health-2000: An Integrated Large-scale Expert System for the Hospital of the Future

1997 ◽  
Vol 36 (02) ◽  
pp. 92-94
Author(s):  
S. F. Boyom ◽  
D. A. Asoh ◽  
C. Asaah ◽  
F. Kengne ◽  
S. Y. Kwankam
Keyword(s):  
Expert System ◽  
Large Scale ◽  
Health Management ◽  
Medical Knowledge ◽  
Sub Saharan Africa ◽  
Equipment Management ◽  
Care Environment ◽  
The Future ◽  
Health Management Information Systems ◽  
Sub Saharan

Abstract:Decision making and management are problems which plague health systems in developing countries, particularly in Sub-Saharan Africa where there is significant waste of resources. The need goes beyond national health management information systems, to tools required in daily micromanagement of various components of the health system. This paper describes an integrated expert system, Health-2000, an information-oriented tool for acquiring, processing and disseminating medical knowledge, data and decisions in the hospital of the future. It integrates six essential features of the medical care environment: personnel management, patient management, medical diagnosis, laboratory management, propharmacy, and equipment management. Disease conditions covered are the major tropical diseases. An intelligent tutoring feature completes the package. Emphasis is placed on the graphical user interface to facilitate interactions between the user and the system, which is developed for PCs using Pascal, C, Clipper and Prolog.

scholarly journals Designing of an Expert system for the management of Seafarer’s health

2020 ◽  
Vol 6 ◽  
pp. 205520762097624
Author(s):  
Gopi Battineni ◽  
Francesco Amenta
Keyword(s):  
Expert System ◽  
Medical Center ◽  
Medical Knowledge ◽  
Epidemiological Data ◽  
Medical Problem ◽  
Design Flow ◽  
Two Phase ◽  
Framework Design ◽  
Medical Issues ◽  
Health Expert

In general merchant ships do not have medical facilities on board. When seafarer got sickness or accident, either ship captain or officers who are in charge will assist them, but these people do not have enough medical knowledge. To overcome this, we developed a Seafarer Health Expert System (SHES) that can facilitate telemedical services in an emergency. A comprehensive analysis of seafarers’ medical issues that were conducted from medical records of patients assisted on board ships by the International Radio Medical Center (C.I.R.M.), Italy. Data mining techniques are involved to manage epidemiological data analysis in a two-phase setup. In the first phase, the common pathologies that occurred onboard were analyzed, later a detailed questionnaire for each medical problem was developed to provide precise symptomatic information to the onshore doctor. In this paper, we mainly highlighted the SHES framework, design flow, and functionality. Besides, nine designing policies and three actors with separate working panels were clearly described. The proposed system is easy and simple to operate for anyone of no computer experience and create medical requests for the fast delivery of symptomatic information to an onshore doctor.

scholarly journals Can Both the Economic Value and Energy Performance of Small- and Mid-Sized Buildings Be Satisfied? Development of a Design Expert System in the Context of Korea

2020 ◽  
Vol 12 (12) ◽  
pp. 4946
Author(s):  
Sean Hay Kim ◽  
Jungmin Nam
Keyword(s):  
Expert System ◽  
Performance Measures ◽  
Economic Value ◽  
Energy Performance ◽  
Rule Base ◽  
Change Scenario ◽  
Design Decision ◽  
Decision Support Model ◽  
Performance Goal ◽  
Design Expert

To design a High-Performance Building (HPB), a performance goal should be clearly set from very early design phases, and then a decision path of what performance measures have been chosen in the past stages and shall be chosen in a later stage should be visible. In particular, for small- and mid-sized HPBs that are constructed with a smaller budget, if applicable performance measures are subjective to change, supplementary design costs can increase due to intermittent performance evaluations. To help this situation, we are developing a design expert system for small- and mid-sized buildings that pursues a balance between economic value and energy performance. The economy rule base suggests the most economic building volumetry and form in view of the site context, while the energy rule base suggests a series of energy-sensitive design variables and their options. Based on these rule bases, the expert system presents multiple design decision paths. The design decision support model of the inference engine helps stakeholders choose a preferred design path out of multiple paths, compare the paths, trace back the paths, and effectively revoke past decisions. An actual small retail and office construction project was chosen as a test case to compare the utility and robustness of the pilot system against the conventional design practice. In case of a rather risky design change scenario, the decision-making using the pilot expert system outperforms the conventional practice in terms of selecting designs with a good balance between economic value and energy performance. In addition, it was easier for users of the pilot system to forecast risks upon critical design changes and, in turn, to identify reasonable alternatives.

Principles and practice in verifying rule-based systems

1992 ◽  
Vol 7 (2) ◽  
pp. 115-141 ◽  
Author(s):  
Alun D. Preece ◽  
Rajjan Shinghal ◽  
Aïda Batarekh
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Order Logic ◽  
First Order Logic ◽  
Rule Based ◽  
First Order ◽  
Rule Bases ◽  
System Knowledge

AbstractThis paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.

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