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Prediction & Classification of Schizophrenia and its Severity Based on Computer Vision, Voice Analysis, and Speech Analysis Captured Remotely Through Smartphone


In this poster you will learn: 

  • Remote digital assessment and diagnosis of schizophrenia and its disease severity using artificial intelligence (AI) over smartphone applications can greatly increase clinical service access
  • Development of novel treatments and clinical trials are limited by a lack of ability to gain insight into patient health and behavior at frequent intervals in non-clinical settings.
  • Facial and verbal features of behavior have been shown to be indicative of clinical functioning in patients with schizophrenia
  • Collection and analysis of facial and verbal features has traditionally required in-person interactions between patients and clinicians followed by tedious manual and often subjective analysis techniques
  • With advancements in machine learning, this analysis can be done in an automated fashion
  • Here, we assess the ability of an interactive smartphone platform to be able to collect data for extraction of facial and verbal features and the ability of those features to be able to distinguish between healthy controls patients with schizophrenia. We also attempt to predict the continuous severity score for both positive and negative symptoms of schizophrenia.