Decoding mental health
one word at a time.
We are pioneering the field of computational language analysis for mental health. Our products automate speech analysis and generate powerful visual graphs that can be used for identifying individuals at risk for mental health disorders and support diagnosis, as well as self-insight.
Can anyone benefit from access to computational language analysis?
Anyone can benefit from having access to visual graphs based on their speech analysis. Simple insights such as word repetition in recurring dream memories can aid psychological treatment and promote new grounds for personal clarity about unconscious patterns and motivations.
What are the dangers of automated mental health diagnosis?
Misdiagnosis is a serious issue that should not be treated lightly. The automation level of our tools is restricted to the translation of speech patterns into visual graphs. Interpretation of our visual data for the purposes of diagnosis should be always done by accredited mental health providers.
How will user privacy and confidentiality be protected?
Psychomeasure has implemented strict measures to ensure that user data remains confidential and secure. All personal information collected by the software is encrypted and stored on secure servers with limited access.
MAKING THE UNCONSCIOUS,
Computational language analysis and machine learning algorithms can be used to analyze patterns in an individual's speech that may indicate underlying psychological distress or unconscious conflicts.
By analyzing patterns and structures in language use, anyone can gain insight into their own thoughts, feelings, and beliefs that may not be readily apparent to the individual themselves. This process of uncovering hidden or repressed aspects of the self can be a powerful tool for personal growth.
Natural language processing tools were applied to study 239 dream reports by 67 individuals.
Assessing speech disorganization during the first clinical contact, as measured by graph connectedness.
Speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews.
Computational language analysis can provide personalized feedback based on underlying emotions and cognitive processes.
By empowering individuals to visualize important elements of their own mental health, we may be able to reduce the burden of mental illness on society as a whole.
User-friendly language analysis tools have the potential to transform the field of mental health care and improve the lives of millions of individuals around the world.
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