Project Type(s):
Clinical Research
Schizophrenia is a prevalent, debilitating psychiatric disorder that is diagnosed based on clinical interviews that are subjective and highly variable; in fact, two patients can have no overlapping symptoms and be diagnosed with the same disease. While cardiologists have blood tests to help diagnose heart attacks and oncologists have PET scans to find hidden cancers, psychiatrists don’t have objective diagnostic tests. This proposal will utilize machine learning to analyze cognitive tests, brain electrical activity, and genetic signatures from 1,415 patients with schizophrenia and 1,062 controls to uncover biomarkers of schizophrenia. By incorporating biomarkers into diagnostic standards, psychiatrists could one day order a simple test that could help them confidently diagnose schizophrenia and make better treatment decisions based on quantitative rather than subjective measures.
Project Period:
September 1, 2024 — August 31, 2025
No
Funding Type(s):
State/UW
Clinician Scientist Training Program
Geographic Area(s):
University of Washington
Practice Type(s):
Outpatient
Patient Population(s):
Adults
Targeted Condition(s):
Psychosis
