A machine learning approach to predicting psychosis using semantic density and latent content analysis

https://www.nature.com/articles/s41537-019-0077-9?fbclid=IwAR20gxqUo9Hf6yDjggvfznO38sbYqLA2HMf5LlFioAb4W2IkTr8z0hQWKxU

A machine learning approach to predicting psychosis using semantic density and latent content analysis
of conversations generated on social media, here 30,000 contributors to Reddit. The results revealed that conversion to psychosis is signaled by low semantic density and talk about voices and sounds. When combined, these two variables were able to predict the conversion with 93% accuracy in the training and 90% accuracy in the holdout datasets. The results point to a larger project in which automated analyses of language are used to forecast a broad range of mental disorders well in advance of their emergence.
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