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This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it.

Human Phenotype Ontology

Human phenotype ontology

Although current diagnostic classifications are clinically useful, their heterogeneous and discrete categories have limited capacity to capture the complexity, granularity, and variability over time of psychopathology; the Human Phenotype Ontology, which operates at the level of observable features, offers a complementary framework.

Psychiatry has relied on classification systems to define and organize mental conditions, guiding clinical decision-making, hospital billing, and translational research; the terms classification, taxonomy, and ontology are often used interchangeably, obscuring important differences in purpose, structure, and epistemic function. By examining these distinctions, the presentation invites a reconsideration of what current systems can and cannot achieve; it highlights the heterogeneous and discrete nature of their categories and their limited capacity to capture the complexity, granularity, and temporal variability of psychopathology, noting that systems such as SNOMED CT face similar challenges when they combine classification, terminology, and phenomenology without sufficient conceptual differentiation. Work conducted within the Human Phenotype Ontology (HPO) framework to represent psychiatric phenomena not only at the level of diagnostic categories but also at the level of observable features will be presented. Drawing on a Delphi process that gathers expert views on the definitions and boundaries of key terms, an ontology of affect and emotion and an ontology of sleep-related phenomena are presented as examples; these examples highlight the need for shared, consensus-based definitions, explicit specification of relationships between concepts, and community-driven refinement of phenomenology. The application of HPO to clinical data will demonstrate its capacity for phenotype-based clustering and the prediction of meaningful outcomes; analyses of symptom severity patterns and change over time will compare phenomenological clusters with categorical diagnoses. The presentation concludes with a collaborative agenda for developing ontological systems that are precise, clinically useful, empirically testable, and reflective of the complexity of clinical psychopathology.

All WCP 2026 summaries