Editor’s note: This article is by Dr. Guillermo Cecchi of IBM Research’s Computational Biology Group.
Analyzing the spoken words of people with mental health disorders could significantly improve the accuracy of diagnosing mania and schizophrenia. In a PLoS ONE paper, my Computational Biology team collaborating with researchers and clinicians in Brazil showed that quantifying and graphing only speech was 93 percent accurate in identifying these cases of psychosis.
This collaboration with professionals across medical, neuroscience, and technical departments at Brazil’s Federal University, and Universidade de Sao Paulo was the first time that psychiatric differential diagnosis was implemented directly from speech analysis. In other words, our study, Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis, was the first to relate thought disorder with mathematical structures – graphs.
|We transcribe the speech to text,|
and create graphs in which nodes
denote words, and edges
between them indicate the
temporal succession of the wor
Diseases such as cancer have clear genomic and proteomic signatures, while psychiatric conditions are more elusive, and may be mostly determined by functional disruptions (problems with our human “software” versus our “hardware”). We set out to show how psychiatry can benefit from computational insights.
So what did we do, and what did we find?
Psychologists at Federal University interviewed hospital patients using standard diagnostic methods, according to the Diagnostic and Statistical Manual of Mental Disorders requirements. The IBM team wanted the text. And after the interviews were manually translated into English, we analytically confirmed – through graphs – the qualitative features of mania and schizophrenia.
Manic graphs are more verbose and contain more loops (when the patient’s train of thought continually return to the same concept) than a normal graph. Schizophrenic graphs are less verbose, but more tangential (when a patient’s focus on one concept consistently changes to many other concepts) than normal.
The difference is purely due to psychiatrists’ use of other factors to make a diagnosis.
Psychosis is part of the spectrum of thought disorders, and the most conspicuous symptoms are expressed in language. Today, the main tool for diagnosis is the personal interview, and a doctor’s assessment of abnormal thought processes reflected in speech.
Words are the most-prominent variables when talking about manic and schizophrenic conditions. We want to establish variables and boundaries – such as the number of words to indicate a condition – that could be put into a technology that will provide clinicians, as well as researchers, with a more quantitative look at their data so that their diagnosis and treatment decisions, which ultimately rest with them, can be better informed.
We are also engaged in extending these initial results to larger cohorts, as well as other modalities of thought and emotional alterations, such as autism and Asperger’s. Preliminary indications show that semantic measures of similarity between words (as opposed to the speech structure revealed by graphs) can be used to help diagnose these other psychiatric conditions that affect emotional processing.