Nathan Cabero, Koshish Shrestha / Mathematics / Faculty Mentor: Ogan Gurel
Psychiatric diagnosis is largely based on symptom assessment, for which a primary resource has been the American Psychiatric Association’s Diagnostic Statistical Manual of Mental Disorders (DSM-5). For diagnosis, the DSM-5 is usually consulted as a “symptom check list”, and, as such, it can be unwieldy to use. These diagnostic criteria are not, however, simple “check lists” but are actually linked together as logical constructs (AND, OR NOT statements), implying a logical underpinning to psychiatric diagnosis, which, in our view, has been underappreciated. In our research we have constructed the “logic circuits” corresponding to the core DSM-5 diagnoses and implemented these in a fully integrated computational engine. This system offers clinicians and researchers significant advantages for accurate and efficient psychiatric diagnosis and diagnosis itself is not novel or difficult, the ability to track which symptom patterns and pathways lead to the diagnosis offers significant possibilities for optimizing and personalizing treatment and prognosis. Our system enables such a capability. In addition, using this logical construction, we have identified mathematical structures in the diagnostic process as well as the “disordered brain” suggesting future lines of work as well as concepts that may inform the next incarnation of diagnostic standards, namely DSM-6.
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