Performance evaluation of rule‐based expert systems: An example from medical billing domain

Abdullah, Umair; Ligęza, Antoni; Zafar, Kashif

doi:10.1111/exsy.12218

Cited by 9 publications

(8 citation statements)

References 22 publications

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“…The production rule is written in the form of conventional if-then statement that is used as conditional control statement in the programming languages. The production rule, however, is based on the dataset and is applied onto the attributes of a database, that makes it different from the if-then used in programming languages [14,17]. Coding in different programming languages requires specialized programming skills, time taken to execute a program, debugging and other incremental costs.…”

Section: If Then mentioning

confidence: 99%

Implementing Rule-based Healthcare Edits

2022

KSII TIIS

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Automated medical claims processing and billing is a popular application domain of information technology. Managing medical related data is a tedious job for healthcare professionals, which distracts them from their main job of healthcare. The technology used in data management has a sound impact on the quality of healthcare data. Most of Information Technology (IT) organizations use conventional software development technology for the implementation of healthcare systems. The objective of this experimental study is to devise a mechanism for use of rule-based expert systems in medical related edits and compare it with the conventional software development technology. A sample of 100 medical edits is selected as a dataset to be tested for implementation using both technologies. Besides empirical analysis, paired t-test is also used to validate the statistical significance of the difference between the two techniques. The conventional software development technology took 254.5 working hours, while rule-based technology took 81 hours to process these edits. Rule-based technology outperformed the conventional systems by increasing the confidence value to 95% and reliability measure to 0.462 (which is < 0.5) which is three times more efficient than conventional software development technology.

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Section: If Then mentioning

confidence: 99%

Implementing Rule-based Healthcare Edits

2022

KSII TIIS

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“…A rule based expert system has made a lot of benefits in billing decision-making. This reduces erroneous claims and claim rejections, increases customer satisfaction, and improves company's revenue as real time performances are also taking place [17]. [18] in their studies found that automation via automated journal entry will reduce repetitive tasks [19] human errors, time consuming and stress, and that journal entry automation could support accountants effectively in all aspects especially data entry and bookkeeping.…”

Section: B Ai Implementation In Invoice Recognition and Automatedmentioning

confidence: 99%

Artificial Intelligence in Automated Bookkeeping: A Value-added Function for Small and Medium Enterprises

Azman

Mohamed

Jamil

2021

JOIV : Int. J. Inform. Visualization

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Bookkeeping plays a vital role in dealing with records of day-to-day financial transactions from invoices until payment. It is also a method of documenting all company transactions in order to create a collection of accounting documents. Studies show that an evolution of bookkeeping management from manual record keeping to electronic record keeping had simplified most burden of bookkeepers as well as more reliable and accurate. Bookkeeping includes, in particular, classifying items correctly and entering financial details into an accounting system. However, with the rise of artificial intelligence, automated bookkeeping system is common to large businesses tasks at real time with hassle free. The system will function more than just journal management but also a decision-making tool to any businesses. Despite the benefits of the system, many small and medium enterprises especially in Malaysia still hesitate to implement the system. Artificial intelligence will further improve automated bookkeeping making it simpler and efficient for all levels of businesses. This paper presents an Artificial Intelligence perspective and methods used in automated bookkeeping focuses on invoices processes such as Optical Character Recognition (OCR), for document recognition, machine learning and auto journal record entries. Besides that, its challenges to be implemented in small and medium enterprise. The result of these studies highlighted benefits in the automated bookkeeping process to suit Malaysian small and medium enterprises. Future work will look at the suggested intelligence features to be implemented for a more efficient automated bookkeeping for small and medium enterprise.

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“…Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity and knowledge storage; the expert systems are part of AI, and in recent times, they are being developed to provide health professionals with support tools for fast and effective diagnosis. [2][3][4] The development of the expert system is carried out through the CLIPS (C Language Integrated Production System); this tool focuses on the development of rules for expert systems. The user interface for data collection is done through a web application which involves the use of Apache, as a Web server, MySQL as a database and PHP as a language for the implementation of the web system.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…6 The accumulation of knowledge about a case under scrutiny allows for solving the problem or helps decide how to complement the information to complete the check-up just as in medical examinations. 2 The MYCIN is one of the earliest rule-based expert system developed by Feigenbaum, Buchanan and Ted Shortliffe in 1970 for the purpose of diagnosis of infectious diseases as support systems for making decisions. A clinical decision support system in healthcare could be based on machine learning for the diagnosis and treatment of respiratory diseases, such as asthma and chronic obstructive pulmonary disease.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development of an expert system for pre-diagnosis of hypertension, diabetes mellitus type 2 and metabolic syndrome

Urrea

Mignogna

2020

Health Informatics J

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This study involved the development of an expert system for the pre-diagnosis of hypertension, diabetes mellitus type 2 and metabolic syndrome. The expert system has been developed using web technologies, PHP, Apache and MySQL with CLIPS tool; the expert system includes three algorithms designed by the authors, one for each disease. The objective of this study is to provide an expert system capable of performing a pre-diagnosis for early detection of hypertension, diabetes mellitus type 2 and metabolic syndrome. The methodology to build the system consists in associated risk factors, clinical variables diagnosis criteria based on World Health Organization standards in three algorithms and then develop a program that interacts with users, besides the expert system is compared with the existing expert systems in order to show its originality and innovation. The rules of systems are designed using CLIPS systems and the Architecture Apache, MySQL and PHP for the user interface and database. The system was validated by 72 patient(s) and 3 real doctors, the total result over 72 patient(s) is low risk 16.6 percent, moderate risk 30.5 percent, moderate high risk 13.8 percent, high risk 23.6 percent, very high risk 15.2 percent, and the doctors’ feedback was similar to that shown by the system. The number of rules to create the algorithms and the criteria used were adequate and sufficient to obtain the pre-diagnosis of each disease; in addition, the languages used to design and create the web application were stable. All users who used the system obtained similar results to those obtained by doctors.

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Performance evaluation of rule‐based expert systems: An example from medical billing domain

Cited by 9 publications

References 22 publications

Implementing Rule-based Healthcare Edits

Implementing Rule-based Healthcare Edits

Artificial Intelligence in Automated Bookkeeping: A Value-added Function for Small and Medium Enterprises

Development of an expert system for pre-diagnosis of hypertension, diabetes mellitus type 2 and metabolic syndrome

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