A Rule-Based Expert System to Assess Coronary Artery Disease Under Uncertainty

Hossain, Sohrab; Sarma, Dhiman; Chakma, Rana Joyti; Alam, Wahidul; Hoque, Mohammed Moshiul; Sarker, Iqbal H.

doi:10.1007/978-981-15-6648-6_12

Cited by 19 publications

(4 citation statements)

References 31 publications

(22 reference statements)

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“…The presented initial system is intended to support and educate patients by making recommendations for Sleep, Physical Activity, BMI, Blood sugar, Mental Health, Heart Health, and Chronic Obstructive Pulmonary Disease issues. The system functions as a ruled based "intelligent agent" [11][12][13], converting the user's data into guidelines for a improving their lifestyle. Domain-specific knowledge is required to model the "environment" where the agent will convert the user's data into recommendations.…”

Section: Methodsmentioning

confidence: 99%

Enriching Remote Monitoring and Care Platforms with Personalized Recommendations to Enhance Gamification and Coaching

Pardos

Gallos

Menychtas

et al. 2023

Studies in Health Technology and Informatics

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Patients’ remote monitoring platforms can be enhanced with intelligent recommendations and gamification functionalities to support their adherence to care plans. The current paper aims to present a methodology for creating personalized recommendations, which can be used to improve patient remote monitoring and care platforms. The current pilot system design is aimed to support patients by providing recommendations for Sleep, Physical Activity, BMI, Blood sugar, Mental Health, Heart Health, and Chronic Obstructive Pulmonary Disease aspects. The users, through the application, can select the types of recommendations they are interested in. Thus, personalized recommendations based on data obtained by the patients’ records anticipated to be a valuable and a safe approach for patient coaching. The paper discusses the main technical details and provides some initial results.

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Section: Methodsmentioning

confidence: 99%

Enriching Remote Monitoring and Care Platforms with Personalized Recommendations to Enhance Gamification and Coaching

Pardos

Gallos

Menychtas

et al. 2023

Studies in Health Technology and Informatics

View full text Add to dashboard Cite

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“…Al-Dmour et al presented the usage of fuzzy logic techniques in a warning system to categorize patients’ status or medical conditions [ 32 ]. RBS and FRBS have also been used to develop many MDSS in recent decades [ 31 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. These systems represent the symptoms of MDSS patients and are based on an inference algorithm to process the information using linguistic terms.…”

Section: Related Workmentioning

confidence: 99%

Comparative Study of Fuzzy Rule-Based Classifiers for Medical Applications

Czmil

2023

Sensors

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The use of machine learning in medical decision support systems can improve diagnostic accuracy and objectivity for clinical experts. In this study, we conducted a comparison of 16 different fuzzy rule-based algorithms applied to 12 medical datasets and real-world data. The results of this comparison showed that the best performing algorithms in terms of average results of Matthews correlation coefficient (MCC), area under the curve (AUC), and accuracy (ACC) was a classifier based on fuzzy logic and gene expression programming (GPR), repeated incremental pruning to produce error reduction (Ripper), and ordered incremental genetic algorithm (OIGA), respectively. We also analyzed the number and size of the rules generated by each algorithm and provided examples to objectively evaluate the utility of each algorithm in clinical decision support. The shortest and most interpretable rules were generated by 1R, GPR, and C45Rules-C. Our research suggests that GPR is capable of generating concise and interpretable rules while maintaining good classification performance, and it may be a valuable algorithm for generating rules from medical data.

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“…It is essential to find out how to meet the increasing demand for electrical energy using a fuzzy expert system. For improved protective performances of the power system, good monitoring of the system in a dynamic state is required, based on a fuzzy interface system [17], [18].…”

Section: Introductionmentioning

confidence: 99%

Application of Forward Chaining Method, Certainty Factor, and Bayes Theorem for Cattle Disease

Putra,

Fadlil,

Umar

2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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Indonesia is a country that has many natural resources, especially mammals. The Papua and West Papua regions are large provinces with abundant natural resources and tremendous livestock potential. The availability of natural resources in the form of live cattle provides a great opportunity to develop animal husbandry in West Papua province. This research was conducted to create a new expert system with a knowledge base to solve the problems that occur and be useful for the community, especially cattle breeders. The current problem is the delay and lack of medical personnel in diagnosing cattle diseases, the distance that must be traveled, which is still very difficult to travel, and the lack of understanding of farmers in early handling when implications indicate animals. So, the Certainty Factor Method and Bayes Theorem with Forward-Chaining search are used to handle current problems. From the results of manual calculations, Certainty Factor Forward Chaining search is a method that has an uncertainty value of 99.84% for 3-day fever compared to Bayes Theorem Forward Chaining search with a value of 50% for worms, 50% for 3-day fever and 50% for nail rot, if applied then Certainty Factor Forward Chaining search is the most appropriate. Likewise, updating the knowledge base must be done from time to time. So that in the future, it can be compared with other methods and Android-based to facilitate current breeders.

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A Rule-Based Expert System to Assess Coronary Artery Disease Under Uncertainty

Cited by 19 publications

References 31 publications

Enriching Remote Monitoring and Care Platforms with Personalized Recommendations to Enhance Gamification and Coaching

Enriching Remote Monitoring and Care Platforms with Personalized Recommendations to Enhance Gamification and Coaching

Comparative Study of Fuzzy Rule-Based Classifiers for Medical Applications

Application of Forward Chaining Method, Certainty Factor, and Bayes Theorem for Cattle Disease

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