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Related Experiment Video

Updated: Jul 10, 2026

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

Published on: May 29, 2026

Managing the Complexity-Coherence Trade-Off in Clinical Reasoning: A Two-Stage Graph Ontology Based on WHO

David Kellett^1,2

¹Rankin Park Centre, John Hunter Hospital, Hunter New England Health, Newcastle, New South Wales, Australia.

Journal of Evaluation in Clinical Practice

|July 8, 2026

Summary

This study introduces a novel two-stage ontological model for clinical reasoning, enhancing cognitive tractability for complex health problems. The model integrates World Health Organization classifications to support clinicians in managing relational complexity.

Keywords:

World Health Organization attitudes and practice clinical reasoning cognitive science complexity disability and health health knowledge international classification of functioning ontology

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A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

Published on: May 29, 2026

Area of Science:

Clinical reasoning research
Health informatics
Ontological modeling

Background:

Contemporary clinical reasoning often involves complex, ill-defined biopsychosocial problems.
Existing models struggle to balance theoretical grounding with practical usability for complex cases.
The World Health Organization Family of International Classifications (WHO-FIC) is rich but not optimized for clinical reasoning.

Purpose of the Study:

To develop a two-stage ontological model based on WHO-FIC.
The model aims for conceptual coherence and cognitive tractability in complex clinical reasoning.
To address limitations of current clinical reasoning frameworks and WHO-FIC.

Main Methods:

Conceptual analysis integrating WHO-FIC theory, clinical reasoning literature, and cognitive theories.
Development of a two-stage, graph-based model to manage complexity and coherence.
Design constraints derived from cognitive theories like bounded rationality and heuristics.

Main Results:

Stage 1: A Body-Activity-Environment triad for problem framing.
Stage 2: Emergent constructs (Health Condition, Participation, Intervention) aligned with WHO-FIC classifications (ICD-11, ICF, ICHI).
The model supports iterative reasoning, managing complexity while preserving diagnostic value.

Conclusions:

The ontology clarifies WHO-FIC ambiguities (e.g., Activity vs. Participation).
It provides a coherent, cognitively usable framework respecting reasoning limits.
Offers a heuristic scaffold for clinicians and educators, advancing clinical reasoning literature.