Treatment Prediction Tools

About

Introduction:

The World Health Organization estimated that around 970 million people worldwide were living with a mental disorder in 2019. In 2020, nearly 53.9 million adults suffered from mental illness in the U.S. Further, it is estimated that over 6 trillion dollars may be spent on treating mental disorders by 2030. The consequence of lack of treatment is significant and it would be helpful to have a tool facilitating psychiatrists with their decisions of diagnosis and prescription. However, some people might react better to stabilizers, while some might respond better to anti-depressants based on individual variations of brain activity and structure, though they both manifest depressive moods. Therefore, there is a need for a tool to aid psychiatrists in determining optimal treatment plans tailored toward a diverse set of patients with comorbidity of depression.

Technology:

Georgia State University researchers developed an artificial intelligence (AI) algorithm to analyze a patient’s fMRI scan and compare it to that of other individuals. This tool can be used by healthcare workers to facilitate the diagnosis of mental disorders, such as depressive disorder and bipolar disorder. Based on the clinical outcomes of those with comparable results, this tool could also predict how a patient would react to one medication versus another, which could be especially useful in patients with unclear mental disorder diagnoses. This tool may help psychiatrists to tailor their treatment recommendations without having the patients try it first. Data has shown that this tool could achieve 90% accuracy in predicting medication outcomes.