Expert System Output Research Articles

An Expert System for Screening and Prognosis of Diseases: An Instance of Healthcare Management

The background of this study is that a Medical Expert System made in Visual Prolog is proposed. This expert system makes a differential diagnosis among heart, lung, kidney, skin, and brain diseases. This system is designed to give help to a medical expert in making the appropriate diagnosis of a patient. Based on a patient's symptoms and medical background, SWI Prolog offers the diagnosis through the declarative knowledge representation methodologies. On the basis of the diagnosis and current medical regulations, it might also offer other treatment options. Medical data analysis using SWI Prolog is used to spot trends or patterns in patient outcomes or disease development. Making better-educated choices concerning patient care and treatment could be made easier by healthcare providers as a result. An SWI Prolog-based medical expert system's output will be influenced by the quality of the data and code used to generate it, as well as by the medical specialists that worked on its design and implementation. The creation of more sophisticated expert systems can be particularly beneficial for early disease detection, helping to reduce the burden of diseases by detecting them more accurately and efficiently.

A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads

AbstractThis paper presents an intelligent speed adaption system for vehicles on conventional roads. The fuzzy logic based expert system outputs a recommended speed to ensure both safety and passenger comfort. This intelligent system includes geometrical features of the road, as well as subjective perceptions of the drivers. It has been developed and checked with real data that were measured with an instrumental system incorporated in a vehicle, on several two‐lane roads located in the Madrid Region, Spain. Along with the road geometrical characteristics, other input variables to the system are external factors, such as weather conditions, distance to the preceding vehicle, tire pressure, and other subjective criteria, such as the desired comfort level, selected by the driver. The expert system output is the most suitable speed for the specific road type, considering real factors that may modify the category of the road and thus, the appropriate speed. This information could be added to the adaptive cruise control of the vehicle. The recommended speed can be a very useful input for both, drivers and the autonomous vehicles, to improve safety on the road system.

Design of the Expert System for Edamame Grading Using Forward Chaining Method

Edamame grade is determined based on edamame quality parameters with several parameters that are quite a lot. The process of deciding edamame grade is relatively complicated and challenging. To determine the edamame grade, an experienced expert in the field is needed. With limited grading experts, the design of expert systems for grading edamame can help users or companies to determine edamame grade. This study aims to design an expert system for determining edamame grade, which can determine the quality of edamame accurately. The Design of an expert system in this research uses the forward chaining method. The stages of designing an expert system include problem identification, knowledge acquisition, building a data flow diagram, compile the database, building a decision tree diagram, and developing a user interface. The results showed that the expert system has been verified and validated well. Verification test results show that all the menu buttons on the expert system application are functioning correctly. Then, the validation results also show that the edamame quality output produced by the expert system is compatible with the expert solution, meaning that the expert system's output data is by following with the results of the decision given by the expert. In testing the validation of determining the quality is appropriate. The results of the verification and validation of the edamame grading expert system show that the expert system has produced satisfactory outcomes. Expert system output is compatible with the solution provided by the expert.

Abstract P4-16-01: Validation of a software based clinical decision support system for breast cancer treatment in a tertiary care cancer center in India

Abstract Introduction: Access to expert, evidence based clinical decision making is crucial in maximizing the outcome of women with breast cancer, but is a scarce resource, especially in developing countries. The Navya Expert System is a patented, software based clinical decision support system that exhaustively searches and assimilates relevant medical literature and guidelines to make specific therapeutic recommendations for individual patients based on their clinical data. This study is a retrospective validation of Navya Expert System's output against tumor board decisions of a multidisciplinary group of expert breast cancer clinicians working in a tertiary care oncology center in India. Methods: Women with non-metastatic breast cancer who had already completed their loco-regional and systemic therapy based on the recommendations of the tumor board were included in the study. The protocol specified clinical and pathology data of these women were retrospectively abstracted from their case charts and processed through the Navya Expert System. The output was classified into major (neo-adjuvant chemotherapy versus upfront surgery and need for adjuvant chemotherapy, endocrine therapy and radiation therapy, respectively) and minor (breast conservation versus mastectomy, taxane versus non-taxane adjuvant chemotherapy and need for nodal radiation therapy) therapeutic decisions. Decisions discordant between the tumor board and the Navya Expert System were adjudicated by an expert panel of breast cancer clinicians from the same institution. Navya Expert System decisions were classified as discordant with appropriate clinical practice if they were in disagreement with both the tumor board and expert panel. All other Navya Expert System decisions were classified as concordant. The primary outcome of the study was concordance between the Navya Expert System and the tumor board or expert panel for major and minor therapeutic decisions. Results: A total of 76 patients involving 224 major and 224 minor therapeutic decisions were included in the study. Navya Expert System's output was concordant with the tumor board or expert review in 224/224 major decisions (100%, 95% CI 99.6%-100%) and 221/224 minor decisions (98.6%, 95% CI 97.1%-100%). Navya Expert System's output was concordant with the tumor board alone in 210/224 (93.75%, 95% CI 90.6%-96.9%) major decisions and 160/224 (71.4%, 95% CI 65.5%-77.3%) minor decisions. Most common reasons for discordance were non-prescription of HER2 targeted therapy by the tumor board due to financial constraints and non-use of nodal radiation for 1-3 node positive patients. Of the 64/224 Navya Expert System decisions discordant with the tumor board, only 3 were finally deemed discordant after review by the expert panel. Conclusions: Navya Expert System treatment recommendations, only requiring the input of commonly available clinical data, are highly concordant with those of a tumor board comprised of breast cancer experts with high level expertise. If these results can be prospectively validated, Navya Expert System has the potential to increase global access to evidence based clinical decision making in breast cancer. Citation Format: Nita Nair, Sudeep Gupta, Naresh Ramarajan, Gitika Srivastava, Vani Parmar, Anusheel Munshi, Shraddha Vanmali, Vaibhav Vanmali, Rohini Hawaldar, Rajendra A Badwe. Validation of a software based clinical decision support system for breast cancer treatment in a tertiary care cancer center in India [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-16-01.

Poster 1001: ALLERGENIUS®: an expert system for the interpretation of allergen microarrays

An expert system, based on Flex, a language related to Prolog, has been developed. The characteristics of the different components and the rules governing the relationships between allergens were obtained from medical literature and specialized web sites. The inputs of the expert system are the age and the diseases of the patient, Skin Prick Tests and specific IgE results (when available) and microarray (ISAC) results. Results The expert system output is represented by a text file containing patient’s identification and the description of the general situation (mono or poly-sensitization, cross- or cosensitization). The patient’s phenotype (Melioli, 2013) and its relationship with expected immunotherapy results (Schmid-Grendelmeier, 2010) are also shown. A list of warnings, related to a sensitization to potentially dangerous components (such as LTPs, Peanuts etc.) is presented. At the end of the introduction, all positive components (inhalants, food, latex and venoms) are listed and commented. Then, families of positive cross-reacting components (such as PR-10, profilins, tropomyosins etc) are discussed. A special section (termed “post molecular anamnesis”) suggest the doctor any clinical questions that should arise from the microarray interpretation (such as the mite-shrimps syndrome in the presence of a sensitization to Der p 10). Finally, two other sections (the first focused on therapeutic suggestions for inhalant allergy and the second of possible discrepancies between SPT /sIgE and microarray results) are available. Of note, the final report has hyperlinks to a dedicated web site to add further information about allergens, component, diseases etc. The “in silico” validation of the expert system (Allergenius v4.2) was successful and the clinical validation in progress.

Study on the Development and Application of Automobile Transmission Design Expert System

This paper introduces the development of transmission design expert system base on MATLAB. It is discussed in detail that the establishment of expert system knowledge base， input and output (I/O) interface， material database and parameter database. In the part of the knowledge base, such as modeling of transmission design calculation, building of material database and parameter database are expounded detailedly. The I/O interface is built with MATLAB “Graphical User Interface (GUI)” technology, which is good at organizing knowledge, so ensure the consistency and rationality between I/O interface and knowledge base. Furthermore, the I/O interface makes the communication between the subsystems more convenience. Finally, with the help of expert system, a (4 + 1) gears Manual Transmission is designed, The result shows that the transmission expert system can shorten automobile transmission design calculating time and improve the calculation precision.

Identification of sport talents using a web-oriented expert system with a fuzzy module

This paper presents a fuzzy expert system for scouting and evaluation of young sport talents. Based on the knowledge of several human sport experts, various motoric skills tests, morphologic characteristics measurements and functional tests are quantized according to their importance for a chosen set of sports. Obtained values are entered into the knowledge database along with the grades of the measured results for each test. Fuzzy logic is implemented in order to make the system more flexible and robust. The whole system is web-oriented, i.e. developed ASP.NET application is available to the internet users with a proper login and password. The developed expert system gives acceptability prediction and proposal of the most suitable sports for the person being tested. The output results of the system were evaluated by 4 experts, using real data collected during several years. Comparison is done between the sport proposed by our expert system and the actual outcome of the person’s sports career. Also, the comparison of the expert system output and the human expert suggestions were done. All tests showed high reliability and accuracy of the developed system. Strengths, possibilities and future plans of the Sport Talent expert system are also discussed.

Development of an expert system for the evaluation of conventional and innovative technologies in the intermodal transport area

The context of this paper concerns the structure of an expert system based modelling tool that was developed and used within the framework of a recent European research project. The objective of the expert system is to produce alternative “technically sound” terminal designs, based on a number of user-defined parameters (cargo volume, loading unit mixture, layout characteristics, operating conditions, etc.) and equipment selections (conventional or innovative transhipment systems, rail access systems, identification, location and positioning devices, semi-automatic control, information systems, etc.). Each of the above “technological bricks” is identified by its “compatibility”, “performance” and “cost” attributes. The “compatibility” and “performance” attributes–through an interactive interface–enable the development of technically sound terminal designs while the “performance” attributes are also used for the calculation of the equipment service cycle. A simulation module converts the equipment service cycle into train service time, as well as into truck service and dwell times, which are then compared to specific quality of service criteria. The cost of the non-rejected designs is calculated (using the “cost” attributes of all involved elements) and together with the draft terminal layout, the area equipment and personnel requirements, form part of the expert system output.

Consideration of the social context of auditors’ reliance on expert system output during evaluation of loan loss reserves

Auditors are accountable for judgments made within the social context of the accounting firm. Tetlock (1985) states that decision makers often use the acceptability heuristic to cope with accountability. According to this heuristic, individuals make decisions which they are reasonably confident will be acceptable by others to whom they are accountable. When auditors form judgments with the aid of expert system output, they must determine the appropriate level of reliance on the expert system output. Since the expert system output is based on the input of experts, auditors may decide the output is ‘acceptable‘ and overrely on the output. In addition, because of the conservative nature of the accounting firm, expert system output which is negative may be viewed as more acceptable than positive output leading to greater overreliance. The results indicate that auditors do overrely on expert system output and rely to a greater degree on output which is negative versus output which is positive. Copyright © 1999 John Wiley & Sons, Ltd.

A combined ANN and expert system tool for transformer fault diagnosis

A combined artificial neural network and expert system tool (ANNEPS) is developed for transformer fault diagnosis using dissolved gas-in-oil analysis (DGA). ANNEPS lakes advantage of the inherent positive features of each method and offers a further refinement of present techniques. The knowledge base of its expert system (EPS) is derived from IEEE and IEC DGA standards and expert experiences to include as many known diagnosis rules as possible. The topology and training data set of its artificial neural network (ANN) are carefully selected to extract known as well as unknown diagnosis correlations implicitly. The combination of the ANN and EPS outputs has an optimization mechanism to ensure high diagnosis accuracy for all general fault types. ANNEPS is database enhanced to facilitate archive management of equipment conditions, trend analysis and further revision of the diagnosis rules, Test results show that the system has better performance than ANN or EPS used individually.

Monitoring expert system performance using continuous user feedback.

To evaluate the applicability of metrics collected during routine use to monitor the performance of a deployed expert system. Two extensive formal evaluations of the GermWatcher (Washington University School of Medicine) expert system were performed approximately six months apart. Deficiencies noted during the first evaluation were corrected via a series of interim changes to the expert system rules, even though the expert system was in routine use. As part of their daily work routine, infection control nurses reviewed expert system output and changed the output results with which they disagreed. The rate of nurse disagreement with expert system output was used as an indirect or surrogate metric of expert system performance between formal evaluations. The results of the second evaluation were used to validate the disagreement rate as an indirect performance measure. Based on continued monitoring of user feedback, expert system changes incorporated after the second formal evaluation have resulted in additional improvements in performance. The rate of nurse disagreement with GermWatcher output decreased consistently after each change to the program. The second formal evaluation confirmed a marked improvement in the program's performance, justifying the use of the nurses' disagreement rate as an indirect performance metric. Metrics collected during the routine use of the GermWatcher expert system can be used to monitor the performance of the expert system. The impact of improvements to the program can be followed using continuous user feedback without requiring extensive formal evaluations after each modification. When possible, the design of an expert system should incorporate measures of system performance that can be collected and monitored during the routine use of the system.

The explanation facility and the explanation effect

The ability to explain reasoning processes used for problem solving distinguishes the expert system from other decision support systems. The explanation facility is intended to help the user critically analyze the expert system output. Studies investigating the explanation effect, however, report that the act of explaining an event's occurrence increases the perceived likelihood of the event. The consideration of expert system explanations, therefore, may lead to greater agreement with the system's output rather than the intended critical review of the output. This research examines the explanation effect resulting from the consideration of expert system explanations. The differential impact of considering expert system explanations is compared to the effect of generating written explanations. In addition, the differential impact of positive versus negative explanations is investigated. A hypothetical audit case was administered to 41 practicing auditors. An explanation effect was observed when the expert system explanation was negative. An explanation effect was not observed when the expert system explanation was positive. An explanation effect was not observed for either positive or negative self-generated explanations. Therefore, the most influential explanations were those which were expert system generated and negative or conservative in direction.

Validation of the Medical Expert System RENOIR

RENOIR is an expert system developed to assist the diagnosis of 37 diseases of connective tissue and inflammatory arthropathies. Precise diagnosis of rheumatic diseases implies great uncertainty and there is no gold standard with which to compare the expert system output. To overcome this problem a set of clinical cases was submitted to RENOIR and its diagnoses were compared with those of clinicians. Medical records or 81 patients with rheumatic diseases were interpreted by RENOIR and by 12 clinicians at three different expertise levels in rheumatology. Distances between the likelihoods of the 37 considered diseases provided by clinicians and RENOIR were computed as a disagreement measure. Mahalanobis distance was used to correct the collinearity between the possibilities of each pair of diseases. Using the resulting matrices of distances between experts, cluster analyses were carried out to classify RENOIR among human experts. Greater differences between RENOIR and clinicians than among clinicians themselves were not found.

Cognitive biases and corrective techniques: proposals for improving elicitation procedures for knowledge-based systems

Expert system output is only as good as the expert judgments on which the system is based. One component of expertise may be defined as the ability to distinguish casual from random occurrence. Judgments of expert and novice alike have been shown to reflect systematic biases in comparison with normative statistical logic. These biases may be important where accuracy, consistency, and coherence are important attributes of the required judgment. Several biases and their cognitive origins are discussed in the context of building knowledge-based systems for wildland fire control. Preliminary guidelines are offered for recognizing and correcting biases during the knowledge-elicitation process.

Development and Validation of an Expert System for Special Educators

The authors describe the development and initial validation of a computer-based expert system, Mandate Consultant (Parry, 1985), designed to review the regulatory procedures for developing Individual Education Programs (IEP). The formative process involved three phases: (a) definition of need and proposed solution, (b) design of a prototype, and (c) progressive refinement through field-testing and revision cycles. The summative component included a two-phase experimental design for validating the accuracy of expert system output through comparisons with human experts. The findings indicated that the expert system-generated conclusions matched the conclusions of the “better” human experts, and were considered more appropriate than the conclusions of the majority of experts. Furthermore, “blinded” evaluators judged the expert system-generated conclusions as being equally acceptable as those produced by the “better” human experts, and more acceptable than those of the majority of experts.