The development of an expert computer system on medical consulation

Area of Science:

• Artificial Intelligence
• Medical Informatics
• Fuzzy Logic Systems

Background:

• Fuzziness and uncertainty pose challenges in human problem-solving.
• Existing expert systems often struggle with inexact reasoning.
• The need for robust systems capable of handling ambiguity is critical in domains like medicine.

Purpose of the Study:

• To develop an expert system shell, SYSTEM Z-II, capable of both exact and inexact reasoning.
• To demonstrate the application of SYSTEM Z-II in building a medical consultation expert system.
• To showcase the system's ability to manage fuzzy human concepts and uncertain factors in medical diagnosis.

Main Methods:

• Development of the SYSTEM Z-II expert system shell.
• Implementation of the ABVAB expert system for Abnormal Vaginal Bleeding diagnosis.
• Utilizing fuzzy logic and inexact reasoning within the expert system framework.
• System development and testing methodologies.

Main Results:

• Successful development of SYSTEM Z-II, an expert system shell handling exact and inexact reasoning.
• Creation of the ABVAB medical expert system demonstrating the shell's power and flexibility.
• The system effectively processes fuzzy human concepts and uncertain factors in the medical domain.

Conclusions:

• The SYSTEM Z-II expert system shell provides a powerful and flexible platform for developing AI systems that handle uncertainty.
• Expert systems like ABVAB, built on such shells, can significantly aid in medical consultations by managing ambiguous information.
• The approach validates the utility of fuzzy logic and inexact reasoning in solving complex, real-world problems.