ESP: An expert system for poisoning diagnosis and management

Abstract

We describe a clinical decision support system (CDSS) designed to provide timely information germane to poisoning. The CDSS aids medical decision making through recommendations to clinicians for immediate evaluation. The system is implemented as a rule-based expert system with two major components: the knowledge base and the inference engine. The knowledge base serves as the database which contains relevant poisoning information and rules that are used by the inference engine in making decisions. This expert system accepts signs and symptoms observed from a patient as input and presents a list of possible poisoning types with the corresponding management procedures which may be considered in making the final diagnosis. A knowledge acquisition tool (KAT) that allows toxicological experts to update the knowledge base was also developed. This article describes the architecture of the fully featured system, the design of the CDSS and the KAT as web applications, the utilisation of the inferencing mechanism of C Language Integrated Production System (CLIPS), which is an expert system shell that helps the system in decision-making tasks, the methods used as well as problems encountered. We also present the results obtained after testing the system and propose some recommendations for future work.

Clinical Decision Support Systems: Effective Solution for Diagnosis, Treatment, and Management of Patients Affected by Poisoning

“…Actually, health professionals in hospitals who handle such cases do not have enough experience and training for the last edition care plan and guidelines to manage those cases. The implementation of the Clinical Decision Support Systems (CDSS) would help alleviate that problem (4).…”

A Laboratory Test Expert System for Clinical Diagnosis Support in Primary Health Care

“…One of the earliest medical expert system, MYCIN [10], provided consultation about infectious disease, diagnosis, and choice of therapy by means of a set of rules. More recent proposals feature Expert System for Poisoning (ESP), which is a rule-based expert system for poisoning diagnosis and management that takes into account signs and symptoms of patients, coming up with a list of possible poisoning types [22].…”

“…This heuristic is similar to the hit ratio of Batista-Navarro et al [22], but our system attributes scores to unknown parameters in order to mitigate issues of incompleteness of data.…”

Machine Learning: A Means of Diagnosing and Prescribing Treatments for Tuberculosis Patients

“…0.33 + 0.53 + 0.5 = eatment) Entropy(Tr (8) 1.36 = eatment) Entropy(Tr (9) Therefore, the Entropy for Treatment is 1.36 shown in (9). Test data comprises of Types of Patient, Type of TB and Type of Smear.…”

“…As stated on the work of Co [7], that this expert system serves as solutions or repeatedly occurring problems. Further, the study of Bautista-Navarro [8] and group motivates the researchers in using 2 major components of an expert system: knowledgebase database and inference engine which contain rules in making decisions. In addition, the study named THESSA [9] uses Database Management System to store and track records in which the researcher also take full advantage of.…”