Collaborative case-based reasoning for knowledge discovery of elders health assessment system

Area of Science:

• Gerontology
• Health Informatics
• Artificial Intelligence

Background:

• Current Elders Health Assessment (EHA) systems lack intelligence and decision support due to single-case-library reasoning.
• Existing systems exhibit poor coordination and limited knowledge reuse capabilities.

Purpose of the Study:

• To propose and implement a collaborative case reasoning framework for EHA knowledge reuse.
• To enhance the intelligence, coordination, and decision support of the EHA system.

Main Methods:

• Developed a multi-case library reasoning application framework for EHA knowledge reuse.
• Utilized XML-based multi-case representation for efficient case organization and retrieval.
• Proposed a Knowledge-Guided Approach with Nearest-Neighbor retrieval algorithm.
• Employed Gray Relational Analysis with weighted Euclidean Distance for improved case similarity measurement.

Main Results:

• The proposed framework facilitates effective knowledge reuse within the EHA system.
• XML-based representation enhances case management and retrieval efficiency.
• The novel retrieval method improves accuracy in complex EHA scenarios.

Conclusions:

• Collaborative case reasoning significantly enhances the EHA system's capabilities.
• The developed framework offers a robust solution for knowledge reuse in health assessment.
• This approach promises improved decision support for elder health care.