The study, published in the journal Depression and Anxiety , found that an AI tool can distinguish with 89 per cent accuracy between the voices of those with or without PTSD. “Our findings suggest that speech-based characteristics can be used to diagnose this disease, and with further refinement and validation, may be employed in the clinic in the near future,” said co-author Charles R. Such AI programmes build “decision” rules and mathematical models that enable decision-making with increasing accuracy as the amount of training data grows. The random forest programme linked patterns of specific voice features with PTSD, including less clear speech and a lifeless, metallic tone, both of which had long been reported anecdotally as helpful in diagnosis. “Speech is an attractive candidate for use in an automated diagnostic system, perhaps as part of a future PTSD smartphone app, because it can be measured cheaply, remotely, and non-intrusively,” said lead author Adam Brown from the varsity.
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