Computational Nosology and Precision Psychiatry
Computational Nosology and Precision Psychiatry
A Proof of Concept
This chapter provides an illustrative treatment of psychiatric morbidity that offers an alternative to the standard nosological model in psychiatry. It considers what would happen if we treated diagnostic categories not as putative causes of signs and symptoms, but as diagnostic consequences of psychopathology and pathophysiology. This reconstitution (of the standard model) opens the door to a more natural formulation of how patients present and their likely response to therapeutic interventions. The chapter describes a model that generates symptoms, signs, and diagnostic outcomes from latent psychopathological states. In turn, psychopathology is caused by pathophysiological processes that are perturbed by (etiological) causes (e.g., predisposing factors, life events, therapeutic interventions). The key advantages of this nosological formulation include: (a) the formal integration of diagnostic categories and latent psychopathological constructs; (b) the provision of a hypothesis or model space that accommodates formal evidence-based hypothesis testing or model selection; (c) the ability to predict therapeutic responses; and (d) a framework that allows one to test hypotheses about the interactions between pharmacological and psychotherapeutic interventions. This chapter shows what might be possible, through the use of idealized simulations. These simulations can be regarded as a (conceptual) prospectus that motivates a computational nosology for psychiatry.
Keywords: Strüngmann Forum Report, nosology, psychiatry, psychopathology, pathophysiology, Bayesian, model selection, dynamics, therapy
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