TB Research

Rules-based Expert System to Assist Physicians in Pre-laboratory Screening for the Diagnosis of Pulmonary Tuberculosis Disease in Rural Areas

Humberto Cuteso Matumueni

Journal of Artificial Intelligence & Cloud Computing · 2022-10

Abstract

Worldwide more than 1.5 to 2 million deaths from tuberculosis occur each year. Healthcare professionals face many challenges in delivering good healthcare with unattended automation in hospitals where multiple patients require physician attention. The expert system we have built is designed to help medical experts in the process of pre-laboratory screening for pulmonary tuberculosis. The architecture consists of a rule base, a patient knowledge base. These units interact with the inference engine, which receives patient data through a user interface. The result of the usability rating reveals that the system has a usability rating of 5.6 on a scale of 1-7. This is an indication of above average system performance. Our Tuberculosis Diagnosis Expert System is an effective solution for implementing a rule-based expert system designed with Exsys Corvid.

MeSH terms

  • Usability
  • Inference engine
  • Expert system
  • Tuberculosis
  • Knowledge base
  • Medicine
  • Rating scale
  • Pulmonary tuberculosis
  • Health care
  • System usability scale
  • Health informatics
  • Computer science
  • Medical emergency