scholarly journals Expert System for Diagnosis of Uterine Myomas using the Certainty Factor Method

2021 ◽  
Vol 1 (4) ◽  
pp. 103-108
Author(s):  
Syahrizal Dwi Putra ◽  
M Bahrul Ulum ◽  
Diah Aryani
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Expert System ◽  
Computer System ◽  
Decision Making Process ◽  
Certainty Factor ◽  
Uterine Myomas ◽  
Factor Method ◽  
Two Factors

An expert system which is part of artificial intelligence is a computer system that is able to imitate the reasoning of an expert with certain expertise. An expert system in the form of software can replace the role of an expert (human) in the decision-making process based on the symptoms given to a certain level of certainty. This study raises the problem that many women experience, namely not understanding that they have uterine myomas. Many women do not understand and are not aware that there are already symptoms that are felt and these symptoms are symptoms of the presence of uterine myomas in their bodies. Therefore, it is necessary for women to be able to diagnose independently so that they can take treatment as quickly as possible. In this study, the expert will first provide the expert CF values. Then the user / respondent gives an assessment of his condition with the CF User values. In the end, the values obtained from these two factors will be processed using the certainty factor formula. Users must provide answers to all questions given by the system in accordance with their current conditions. After all the conditions asked are answered, the system will display the results to identify that the user is suffering from uterine myoma disease or not. The Expert System with the certainty factor method was tested with a patient who entered the symptoms experienced and got the percentage of confidence in uterine myomas/fibroids of 98.70%. These results indicate that an expert system with the certainty factor method can be used to assist in diagnosing uterine myomas as early as possible.

scholarly journals Diagnose Expert System Computer Malfunction Certainty Factor Method

2020 ◽  
Vol 2 (1) ◽  
pp. 63-71
Author(s):  
Djouking Kiray ◽  
Fricles Ariwisanto Sianturi
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Base System ◽  
Certainty Factor ◽  
Factor Method ◽  
Knowledge Base System ◽  
Two Factors ◽  
Computer Based

An expert system is a knowledge base system that solves problems using an expert's knowledge that is entered into a computer, thereby increasing productivity, Because an expert can work faster than a human lay works like an expert. Expert systems Also solve problems by imitating the ways in the which an expert expert offer section with problems in his field, one of the which is in the field of computer repair, the problem of computer damage Becomes a fairly complicated problem, this problem is Generally experienced by individuals and institutions. One of them is in school institutions that have computer laboratories. to diagnose computer use can damage the certainty factor method that helps identify damage to the computer and find the cause of damage to the computer based on the symptoms that occur and the solution to repair it. Certainty Factor is one of the techniques used to deal with uncertainty in decision making. In dealing with a problem, answers are Often found that do not have full certainty. This uncertainty is influenced by two factors items, namely the uncertain rules and user uncertain answers. Uncertain rules are rules of symptoms that are determined for a damage.

scholarly journals Rancang Bangun Sistem Pakar Diagnosa Penyakit Tanaman Stroberi Menggunakan Metode Certainty Factor Berbasis Web

Repositor ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 47
Author(s):  
Nina Mauliana Noor Fajriah ◽  
Yufis Azhar ◽  
Gita Indah Marthasari
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Computer Science ◽  
Programming Language ◽  
Disease Symptom ◽  
Certainty Factor ◽  
Factor Method ◽  
System Database ◽  
And Behavior

Expert system is one of the AI Development fields. AI (Artificial Intelligence) is part of a computer science which used the computer to imitate the human thoughts and behavior. The usage of a method in Expert System is very important. Thus, the most compatible method to use is the Certainty Factor method. This method is suitable to be used on Expert System to measure things and diagnosed it, will it be very sure or unsure. For example, Expert System to diagnose disease on strawberry plants. This software allows the user to diagnose the disease on strawberry plants before taking a further action. This software is using PHP programming language and store the data using MySQL system database. When the user consulting to the software, the software will show the symptoms of the disease and the user can choose the level of certainty from the chosen disease symptom. The final result from the software is a form which includes the guide of how to take the measurement of the disease based on the chosen symptoms.

Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence

2021 ◽  
Author(s):  
Ekaterina Jussupow ◽  
Kai Spohrer ◽  
Armin Heinzl ◽  
Joshua Gawlitza
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Medical Errors ◽  
Decision Makers ◽  
Medical Decision ◽  
Decision Making Process ◽  
Self Monitoring ◽  
Rule Based ◽  
Human Actors

Systems based on artificial intelligence (AI) increasingly support physicians in diagnostic decisions, but they are not without errors and biases. Failure to detect those may result in wrong diagnoses and medical errors. Compared with rule-based systems, however, these systems are less transparent and their errors less predictable. Thus, it is difficult, yet critical, for physicians to carefully evaluate AI advice. This study uncovers the cognitive challenges that medical decision makers face when they receive potentially incorrect advice from AI-based diagnosis systems and must decide whether to follow or reject it. In experiments with 68 novice and 12 experienced physicians, novice physicians with and without clinical experience as well as experienced radiologists made more inaccurate diagnosis decisions when provided with incorrect AI advice than without advice at all. We elicit five decision-making patterns and show that wrong diagnostic decisions often result from shortcomings in utilizing metacognitions related to decision makers’ own reasoning (self-monitoring) and metacognitions related to the AI-based system (system monitoring). As a result, physicians fall for decisions based on beliefs rather than actual data or engage in unsuitably superficial evaluation of the AI advice. Our study has implications for the training of physicians and spotlights the crucial role of human actors in compensating for AI errors.

scholarly journals Android Based Expert System Application for Diagnose COVID-19 Disease: Cases Study of Banyumas Regency

2020 ◽  
Vol 1 (2) ◽  
pp. 26
Author(s):  
Rosyid Ridlo Al Hakim ◽  
Erfan Rusdi ◽  
Muhammad Akbar Setiawan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Confidence Level ◽  
Certainty Factor ◽  
Global Pandemic ◽  
Android Os ◽  
The Status

Since being confirmed by WHO, the status of COVID-19 outbreak has become a global pandemic, the number of cases has been confirmed positive, cured, and even death worldwide. Artificial intelligence in the medical has given rise to expert systems that can replace the role of experts (doctors). Tools to detect someone affected by COVID-19 have not been widely applied in all regions. Banyumas Regency, Indonesia is included confirmed region of COVID-19 cases, and it’s difficult for someone to know the symptoms that are felt whether these symptoms include indications of someone ODP, PDP, positive, or negative COVID-19, and still at least a referral hospital handling COVID-19. Expert system with certainty factor can help someone make a self-diagnose whether including ODP, PDP, positive, or negative COVID-19. This expert system provides ODP diagnostic results with a confidence level of 99.96%, PDP 99.99790%, positive 99.9999997%, negative 99.760384%, and the application runs well on Android OS

scholarly journals Expert System Diagnose Disease in Poultry Using Certainty Factor Method

2020 ◽  
Vol 2 (1) ◽  
pp. 167-170
Author(s):  
Oktavio Nansia ◽  
Bosker Sinaga
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Computational Method ◽  
Certainty Factor ◽  
Factor Method ◽  
Lack Of Information ◽  
Artifical Intelligence ◽  
System Method ◽  
The Times ◽  
Inexact Reasoning

In this study, the authors conducted research to apply the Certainty Factor Method to Diagnose Diseases in Livestock and build applications in the application of Reviews These methods. Information technology is now a staple in developing a field. Along with the development of the times, proper information management is needed, so we need an Appropriate computational method. In this case the expert system method is one way to find out or identify diseases in poultry that have been infected with bacteria or viruses. A form of management information system specifically created to support a plan in making decisions to solve a case or problem. Artificial Intelligence (Artifical Intelligence) is one part of computer science that makes machines (computers) can do work as and as well as humans do. Expert System is one of the Artificial Intelligence techniques that attempts to adopt human knowledge into computers, so that computers can solve problems as is usually done by experts. Diagnosing disease in poultry is currently a problem that is still underestimated for most people, this is due to lack of knowledge or lack of information in terms of Overcoming and Preventing Contaminated, viruses or bacteria. Certainty Theory Theory was suggested by Shortlife and Buchanan in 1975 to a accommodate the uncertainty of thinking or inexact reasoning of an expert. Phrases like "maybe", "most likely", "almost Certain". To a accommodate this, Researchers conducted a certainty factor method to describe the level of expert confidence in problems in diseases Suffered by chickens already infected with dangerous viruses.

scholarly journals Analisis Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit THT

2018 ◽  
Vol 10 (1) ◽  
pp. 30-35 ◽  
Author(s):  
Khairina Eka Setyaputri ◽  
Abdul Fadlil ◽  
Sunardi Sunardi
Keyword(s):  
Decision Making ◽  
Infected Person ◽  
Certainty Factor ◽  
Web Based ◽  
Factor Method ◽  
Two Factors ◽  
Clear Information ◽  
Nose And Throat ◽  
Require Information

There are two factors that cause a disease, called  Congenital and Acquired. Congenital refers to a disease a person is born with, while Acquired refers to a disease acquired after a person was born such as infection, trauma, and neoplasm. The infected person will sometimes require information on the disease before going to the doctor or a hospital. Such information may be found from a system which receives input on the symptoms and gives a clear information on the corresponding disease. This may be achieved via a system of experts, in which the expert refers to an ENT (Ear, Nose, and Throat) specialist. Such information is hoped to provide a solution on the disease. The system of ENT specialists designed and research in this paper used the certainty factor method. The method will overcome the uncertainty in decision making depending on the symptoms described by the user. This paper is successfully applied certainty factor method used as an instrument of decision making in the system of ENT specialists. The system is web-based, enabling the user to access and choose the symptoms of the disease as well as acquiring information on ENT diseases  easly.

scholarly journals Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases

2018 ◽  
Vol 2 (1) ◽  
pp. 32
Author(s):  
Erwin Kuit Panggabean
Keyword(s):  
Artificial Intelligence ◽  
Comparative Analysis ◽  
Expert System ◽  
Knowledge Representation ◽  
Programming Languages ◽  
Certainty Factor ◽  
Factor Method ◽  
System Method ◽  
Artificial Intelligence Technology ◽  
Better Than

The development of artificial intelligence technology that has occurred has allowed expert systems to be applied in detecting disease using programming languages. One in terms of providing information about a variety of disease problems that have recently been feared by Indonesian society, namely stroke. Expert system method used is dempster shafer and certainty factor method is used to analyze the comparison of both methods in stroke.Based on the analysis result, it is found that certainty factor is better than demster shafer and more accurate in handling the knowledge representation of stoke disease according to the symptoms of disease obtained from one hospital in medan city, uniqueness of algorithm that exist in both methods.

scholarly journals How do experts recognize schizophrenia: the role of the disorganization symptom

2006 ◽  
Vol 28 (1) ◽  
pp. 5-9 ◽  
Author(s):  
Denise Razzouk ◽  
Jair de Jesus Mari ◽  
Itiro Shirakawa ◽  
Jacques Wainer ◽  
Daniel Sigulem
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Clinical Reasoning ◽  
Clinical Decision Making ◽  
Cognitive Model ◽  
Clinical Decision ◽  
Reasoning Patterns

OBJETIVE: Research on clinical reasoning has been useful in developing expert systems. These tools are based on Artificial Intelligence techniques which assist the physician in the diagnosis of complex diseases. The development of these systems is based on a cognitive model extracted through the identification of the clinical reasoning patterns applied by experts within the clinical decision-making context. This study describes the method of knowledge acquisition for the identification of the triggering symptoms used in the reasoning of three experts for the diagnosis of schizophrenia. METHOD: Three experts on schizophrenia, from two University centers in Sao Paulo, were interviewed and asked to identify and to represent the triggering symptoms for the diagnosis of schizophrenia according to the graph methodology. RESULTS: Graph methodology showed a remarkable disagreement on how the three experts established their diagnosis of schizophrenia. They differed in their choice of triggering-symptoms for the diagnosis of schizophrenia: disorganization, blunted affect and thought disturbances. CONCLUSIONS: The results indicate substantial differences between the experts as to their diagnostic reasoning patterns, probably under the influence of different theoretical tendencies. The disorganization symptom was considered to be the more appropriate to represent the heterogeneity of schizophrenia and also, to further develop an expert system for the diagnosis of schizophrenia.

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