"Auctoritas" psychiatric expert system shell

Area of Science:

• Computer Science in Medicine
• Psychiatric Informatics
• Artificial Intelligence in Healthcare

Background:

• Existing healthcare systems lack integrated administrative, diagnostic, and therapeutic functions.
• A unified system is needed for efficient patient management and long-distance follow-up.
• Standardized psychiatric nosology is crucial for accurate diagnosis and research.

Purpose of the Study:

• To develop a universal computer expert system, "Auctoritas," for comprehensive psychiatric patient management.
• To enable long-distance patient follow-up and support clinical and scientific work.
• To create a system compatible with international diagnostic standards like DSM and ICD.

Main Methods:

• Developed a four-part system: Administration, Diagnostic Decision Support, Treatment Activities, and Statistics.
• The Diagnostic Decision Support System utilizes fuzzy logic and backward chaining for enhanced accuracy.
• Incorporated symptom scaling, importance sorting, and reliability-validity results for a flexible diagnostic approach.

Main Results:

• The "Auctoritas" system integrates patient data, administrative tasks, and diagnostic support.
• It facilitates homogeneous and up-to-date psychiatric nosology aligned with DSM-IV and ICD-X.
• The system supports patient scheduling, treatment monitoring, and versatile statistical data analysis.

Conclusions:

• "Auctoritas" serves as a global database and advisory system for managing hospital networks.
• It enables continuous, individualized, long-distance patient observation and centralizes patient information.
• The system aids physicians in compiling and processing data for scientific research and publications.