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.
Wow - Fascinating! Very cool research - would love to see this in a Documentary!
ReplyDeleteI would like to know the problems associated with the word 'schizophrenia'. Mainly negative conotations that come with it(schizo). Can someone direct me to a useful website??
ReplyDeleteAlso the word 'patient' the verb. I would like to know the negative conotations that come with it. I am researching stuff on medical and social model languages.
ReplyDelete