scholarly journals Rule-Based Expert System for Assist Physician to Diagnosis of Malaria: XPerMal

2021 ◽  
pp. 35-43
Author(s):  
Humberto Cuteso Matumueni
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Health Professionals ◽  
Rural Areas ◽  
Medical Sciences ◽  
Medical Expert ◽  
Rule Based ◽  
Medical Expertise ◽  
Common Diseases ◽  
Reasoning Strategy

Nowadays, common diseases like malaria, typhoid and cholera become more dangerous problems for people living in this world. The objective is how it can avoid the queue of patients in hospital. In this article, the author has proposed a model of expert systems using the knowledge of physician and other health professionals. The rule based expert system XPerMal useful for patients infected with common diseases and this system will give an answer as similar to a doctor or medical expert and also this system is very useful in rural areas where we have young medical experts or have no medical expert. The reasoning strategy is a key element in many medical tasks. It is well known that developing countries face a shortage of medical expertise in the medical sciences. Patients also find a huge queue in hospitals. Because of this, they are unable to provide good medical services to their inhabitants. The knowledge is acquired from literature review and human experts in the specific field and is used as a basis for analysis, diagnosis and decision-making. Knowledge is represented by an integrated formalism that combines rules and facts.

scholarly journals Optimization Model of Fuzzy Rule Based Expert System Using Max-Min Composition and Schema Mapping Translation

INSIST ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 30 ◽  
Author(s):  
Hartono Hartono ◽  
Tiarma Simanihuruk
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Expert System ◽  
Membership Function ◽  
Fuzzy Rule ◽  
Fuzzy Decision Making ◽  
Schema Mapping ◽  
Fuzzy Decision ◽  
Rule Based ◽  
Knowledge Based

Abstract— Fuzzy Decision Making involves a process of selecting one or more alternatives or solutions from a finite set of alternatives which suits a set of constraints. In the rule-based expert system, the terms following in the decision making is using knowledge based and the IF Statements of the rule are called the premises, while the THEN part of the rule is called conclusion. Membership function and knowledge based determines the performance of fuzzy rule based expert system. Membership function determines the performance of fuzzy logic as it relates to represent fuzzy set in a computer. Knowledge Based in the other side relates to capturing human cognitive and judgemental processes, such as thinking and reasoning. In this paper, we have proposed a method by using Max-Min Composition combined with Genetic Algorithm for determining membership function of Fuzzy Logic and Schema Mapping Translation for the rules assignment.Keywords— Fuzzy Decision Making, Rule-Based Expert System, Membership Function, Knowledge Based, Max-Min Composition, Schema Mapping Translation

scholarly journals Implementation constraints and opportunities in developing expert system solutions for diagnosis of common diseases found in Taraba State

2018 ◽  
Vol 4 (3) ◽  
pp. 18
Author(s):  
Aliyu Sani Ahmad
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Clinical Observation ◽  
Fuzzy Expert System ◽  
Medical Field ◽  
Common Diseases ◽  
Information And Communication

Digital age has reform decision making especially in medical field through information and communication technology which become inevitable part of our lives. this paper illustrates the implementation constraint that encompasses developing Fuzzy Expert System (FES) for diagnosis of common diseases usually found in Taraba State. The paper, shows how fuzzy expert works through four distinct phases. It is discovered that the ratio of doctors to patients and the ratio of hospitals to doctors in Taraba is too low. Different literature that discussed how expert systems for diagnosing various diseases were reviewed; Interview, clinical observation, asking question and internet services were used as methodology for accomplishing this paper.  Result were illustrated and finally conclusion was drowned which shows that e-medical solution for diagnosing disease would do well in Taraba because of the opportunities it offers but it loaded with challenges and implementation constraint.

scholarly journals DIAGNOSA PENYAKIT PADA KAMBING DENGAN SISTEM PAKAR BERBASIS ANDROID

Respati ◽  
2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Muhammad Rizki Setyawan ◽  
Andika Agus Slameto
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Rural Areas ◽  
Search Technique ◽  
Early Disease ◽  
Forward Chaining ◽  
Very High

INTISARIPengetahuan yang kurang akan penyakit pada kambing ditengah masyarakat dalam upaya identifikasi awal penyakit mempengaruhi pengambilan keputusan secara mandiri. Ketergantungan terhadap pengetahuan seorang pakar atau dokter hewan sangatlah tinggi, tetapi keberadaannya tidak selalu ada dan sangat susah ditemui, terutama di daerah pedesaan. Ditambah dengan masalah biaya dan sangat tidak efisien dari segi waktu.Oleh karena itu dalam penelitian ini dirancang sebuah sistem pakar dengan metode forward chaining yang merupakan teknik pencarian dimulai dari fakta yang diketahui, kemudia mencocokkan fakta-fakta tersebut dengan bagian IF dari rule IF-THEN. Bila ada fakta yang cocok dengan bagian IF, maka rule tersebut dieksekusi sebagai penarik kesimpulan untuk mendiagnosa penyakit pada kambing.Aplikasi sistem pakar dibuat berbasis Android karena penggunanya yang banyak dan dapat mudah digunakan dimana saja dan kapan pun. Diharapkan aplikasi dapat memberikan solusi dan penanganan sementara pada ternak berupa panduan untuk mengantisipasi terjadinya kematian pada kambing sebelum ditanyakan langsung kepada seorang pakar untk penanganan lebih lanjut.Dengan adanya sistem pakar untuk diagnose penyakit pada kambing berbasis android ini maka memudahkan peternak dalam melakukan tindakan yang diperlukan secara tepat dalam menangani penyakit pada kambing.Kata kunci:  Android, penyakit, sistem pakar, forward chaining, kambing, android, mobile ABSTRACTLow knowledge of goat disease in the community in an attempt to identify early disease affects decision-making independently. Dependence on the knowledge of an expert or veterinarian is very high, but its existence is not always present and very difficult to find, especially in rural areas. Coupled with cost issues and very inefficient in terms of time.Therefore in the study designed an expert system with forward chaining method which is a search technique starting from known facts, then match those facts with the IF part of the IF-THEN rule. If there are facts that match the IF section, then the rule is executed as a conclusion to diagnose the disease in goats.Expert system applications are made based on Android because of its many users and can be easy to use anywhere and anytime. It is expected that the application can provide solutions and temporary handling of livestock in the form of a guide to anticipate the occurrence of death in goats before being asked directly to an expert for further handling.With the expert system for diagnosis of disease in goats android-based this makes it easier for farmers in performing the necessary actions appropriately in dealing with disease in goats.Keywords : android, disease, expert system, forward chaining,  goat, android, mobile.

The Consistency of the Medical Expert System CADIAG-2

2011 ◽  
Vol 4 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Pavel Picado Klinov ◽  
Bijan Parsia ◽  
David Muiño
Keyword(s):  
Internal Medicine ◽  
Expert System ◽  
Knowledge Base ◽  
Probabilistic Logic ◽  
Large Collection ◽  
Medical Expert ◽  
Rule Based ◽  
Medical Expert System ◽  
Conditional Statements ◽  
Medical Diagnose

CADIAG-2 is a well known rule-based medical expert system aimed at providing support in medical diagnose in the field of internal medicine. Its knowledge base consists of a large collection of IF-THEN rules that represent uncertain relationships between distinct medical entities. Given this uncertainty and the size of the system, it has been challenging to validate its consistency. Recent attempts to partially formalize CADIAG-2’s knowledge base into decidable Gödel logics have shown that, on formalization, the system is inconsistent. In this paper, the authors use an alternative, more expressive formalization of CADIAG-2’s knowledge base as a set of probabilistic conditional statements and apply their probabilistic logic solver (Pronto) to confirm its inconsistency and compute its conflicting sets of rules under a slightly relaxed interpretation. Once this is achieved, the authors define a measure to evaluate inconsistency and discuss suitable repair strategies for CADIAG-2 and similar systems.

The Consistency of the Medical Expert System CADIAG-2

2013 ◽  
pp. 1-20 ◽  
Author(s):  
Pavel Picado Klinov ◽  
Bijan Parsia ◽  
David Muiño
Keyword(s):  
Internal Medicine ◽  
Expert System ◽  
Knowledge Base ◽  
Probabilistic Logic ◽  
Large Collection ◽  
Medical Expert ◽  
Rule Based ◽  
Medical Expert System ◽  
Conditional Statements ◽  
Medical Diagnose

CADIAG-2 is a well known rule-based medical expert system aimed at providing support in medical diagnose in the field of internal medicine. Its knowledge base consists of a large collection of IF-THEN rules that represent uncertain relationships between distinct medical entities. Given this uncertainty and the size of the system, it has been challenging to validate its consistency. Recent attempts to partially formalize CADIAG-2’s knowledge base into decidable Gödel logics have shown that, on formalization, the system is inconsistent. In this paper, the authors use an alternative, more expressive formalization of CADIAG-2’s knowledge base as a set of probabilistic conditional statements and apply their probabilistic logic solver (Pronto) to confirm its inconsistency and compute its conflicting sets of rules under a slightly relaxed interpretation. Once this is achieved, the authors define a measure to evaluate inconsistency and discuss suitable repair strategies for CADIAG-2 and similar systems.

Overcoming deficiencies of the rule-based medical expert system

1990 ◽  
Vol 32 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Christopher A. Hughes ◽  
Earl E. Gose ◽  
David L. Roseman
Keyword(s):  
Expert System ◽  
Medical Expert ◽  
Rule Based ◽  
Medical Expert System

Rule-Based Expert System versus Novices' Heuristics: A Matching Identification Problem

1998 ◽  
Vol 82 (3_suppl) ◽  
pp. 1423-1431
Author(s):  
A. Mehrez ◽  
G. Steinberg
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Identification Problem ◽  
Search Strategies ◽  
Problem Size ◽  
Rule Based ◽  
System Versus ◽  
Encoding And Retrieval

The present study focused on encoding and retrieval of knowledge as aids to decision-making by comparing the performance of rule-based expert systems and novices' heuristics within the framework of a matching identification problem. A rule-based expert system is developed with a computerized controlled procedure to evaluate and compare its performance with search strategies employed by novices. Analysis indicated that, as problem size increased, the system's outcome compared to novices' heuristics is improved.

Prioritization of congenital cardiac surgical patients using fuzzy reasoning – a solution to the problem of the waiting list?

2006 ◽  
Vol 16 (3) ◽  
pp. 289-299 ◽  
Author(s):  
Ralf Holzer ◽  
Ed Ladusans ◽  
Denise Kitchiner ◽  
Ian Peart ◽  
Gordon Gladman ◽  
...  
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Production System ◽  
Medical Decision Making ◽  
Waiting List ◽  
Surgical Patients ◽  
Medical Decision ◽  
Impact Factors ◽  
Decision Making Process ◽  
Rule Based

Surgical waiting lists are of high importance in countries, where the national health system is unable to deliver surgical services at a rate that would allow patients to avoid unnecessary periods of waiting. Prioritization of these lists, however, is frequently arbitrary and inconsistent.The objective of our research was to analyze the medical decision-making process when prioritizing patients with congenital cardiac malformations for cardiac surgical procedures, identifying an appropriate representation of knowledge, and transferring this knowledge onto the design and implementation of an expert system (“PrioHeart”).The medical decision-making process was stratified into three stages. The first was to analyze the details of the procedure and patient to define important impact factors on clinical priority, such as the risk of adverse events. The second step was to evaluate these impact factors to define an appropriate “timing category” within which a procedure should be performed. The third, and final, step was to re-evaluate the characteristics of individual patients to differentiate between those in the same timing category.We implemented this decision-making process using a rule-based production system with support for fuzzy sets, using the FuzzyCLIPS inference engine and expert system shell as a suitable development environment for the knowledge base.The “PrioHeart” expert system was developed to give paediatric cardiologists a tool to allow and facilitate the prioritization of patients on the cardiosurgical waiting list. Evaluation of “PrioHeart” on limited sets of patients documented appropriate results of prioritization, with a significant correlation between the prioritization made using “PrioHeart” and those results obtained by the individual consultant specialist.We conclude that our study has demonstrated the feasibility of using an expert system approach with a fuzzy, rule-based production system to implement the prioritization of cardiac surgical patients. The approach may potentially be transferable to other medical subspecialities.

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