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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Knowledge modeling tool for evidence-based design.

Sanja Durmisevic¹, Ozer Ciftcioglu

¹Faculty of Architecture, Delft University of Technology, Julianalaan 134, 2628 BL Delft, the Netherlands. s.durmisevic@ipact.nl

|December 18, 2010

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This study introduces a computational model to manage the complexity of evidence-based design (EBD) in healthcare environments. The model integrates existing and new knowledge to estimate design performance and support decision-making for better patient outcomes.

Area of Science:

Healthcare Design
Evidence-Based Design (EBD)
Computational Modeling

Background:

The rapid growth of knowledge in EBD creates complexity, making it challenging to consider all design features simultaneously.
Existing EBD approaches struggle to manage the information explosion and its impact on healthcare building performance.

Purpose of the Study:

To develop a framework for a performance-based measurement tool to support healthcare environment design and evaluation.
To create a computational model that integrates diverse design features and knowledge for efficient use by the design community.

Main Methods:

Structured evidence using a "fuzzification" process.
Calculated variable weights via analytical hierarchy process.
Modeled knowledge using a fuzzy neural tree structure and assessed impact with sensitivity analysis.

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Main Results:

The proposed model effectively handles complex, interrelated variables in healthcare design.
It integrates existing and new evidence into a knowledge tree for a coordinated approach.
The model facilitates understanding of design interventions' effects on overall performance.

Conclusions:

The developed model offers a manageable approach to the information explosion in EBD.
It provides decision support for optimizing healthcare environments by estimating design performance.
The framework enables the integration of knowledge for improved planning and design outcomes.