By By Tim Sandle May 5, 2019 in Science Artificial intelligence can be used to assess whether a person is suffering from post-traumatic stress disorder through an analysis of the subject’s voice patterns, noting and processing any variations to predict the medical diagnosis. The study comes from the NYU Langone Health and NYU School of Medicine, where the researchers used a specially designed computer program to assess the stress levels of veterans by analyzing their voices. The key findings have been presented to the conference of the International Speech Communication Association. Conventionally post-traumatic stress disorder by clinical interviews or self-assessment. This can prove to be a lengthy and variable process, which was partly the reason for training artificial intelligence as well as the remote medical reasons. To develop the technology, The first step with the development of the technology involved recording standard long-term diagnostic interviews (which are classed as Each of the recordings was added into the voice software and this produced a total of 40,526 short speech voices. These were used to train the artificial intelligence. Once trained, the technology was then tested with a new set of subjects, who were known to the researchers and some of who had been assessed as having post-traumatic stress disorder. The next aim is to introduce the artificial intelligence into the clinical setting. Commenting on the study, The output from the study has been The research is not only useful at close quarters, it also offers a potential telemedical approach to use applied to the assessment of patients located in remote areas and away from specialist medical facilities.The study comes from the NYU Langone Health and NYU School of Medicine, where the researchers used a specially designed computer program to assess the stress levels of veterans by analyzing their voices. The key findings have been presented to the conference of the International Speech Communication Association.Conventionally post-traumatic stress disorder by clinical interviews or self-assessment. This can prove to be a lengthy and variable process, which was partly the reason for training artificial intelligence as well as the remote medical reasons.To develop the technology, the scientists used a statistical and machine learning tool termed 'random forest'. This form of artificial intelligence has the ability to "learn" how to classify individuals based in learnt examples and using decision-making rules together with mathematical models.The first step with the development of the technology involved recording standard long-term diagnostic interviews (which are classed as PTSD Scales under Clinician's Checks ) with 53 U.S. veterans from campaigns in Iraq and Afghanistan, who has been assessed as suffering from different forms of post-traumatic stress disorder. These were compared with interviews with 78 non-ill veterans.Each of the recordings was added into the voice software and this produced a total of 40,526 short speech voices. These were used to train the artificial intelligence. Once trained, the technology was then tested with a new set of subjects, who were known to the researchers and some of who had been assessed as having post-traumatic stress disorder. The next aim is to introduce the artificial intelligence into the clinical setting.Commenting on the study, lead scientist Dr. Charles R. Marmar notes : “Our findings suggest that speech characteristics can be used to diagnose this disease, and with further training and confirmation, they can be used in the clinic in the near future.”The output from the study has been published in the journal Depression and Anxiety, with the research study titled “Speech‐based markers for posttraumatic stress disorder in US veterans.” More about pstd, posttraumatic stress disorder, Artificial intelligence, Medical, Voice recognition More news from pstd posttraumatic stress... Artificial intellige... Medical Voice recognition