An integrated system to represent and manage medical knowledge

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Knowledge Representation

Background:

• Managing complex specialist medical knowledge is challenging.
• Existing systems may lack integration or flexibility.
• Formalizing medical expertise is crucial for decision support.

Purpose of the Study:

• To describe an integrated system for creating and managing medical knowledge bases.
• To formalize specialist medical knowledge using production rules and frames.
• To enable efficient data and knowledge management within a MUMPS database.

Main Methods:

• Developed an integrated system using Prolog.
• Employed production rules and frames for knowledge formalization.
• Utilized M Technology (MUMPS) for database management.

Main Results:

• The system successfully integrates knowledge representation formalisms (rules, frames) with a database.
• It allows for the creation of personal knowledge bases in medicine.
• Data and knowledge are effectively managed within the MUMPS database.

Conclusions:

• The integrated Prolog system provides a robust platform for medical knowledge engineering.
• This approach facilitates the formalization and management of specialist medical knowledge.
• The system demonstrates the feasibility of combining AI techniques with existing database technologies for medical applications.