mothra wrote on Apr 19
th, 2020 at 1:21pm:
aquascoot wrote on Apr 19
th, 2020 at 1:16pm:
white flag accepted
Last year, many members of this research team were able to show that analysis of Facebook posts could predict a diagnosis of depression as much as three months earlier than a diagnosis in the clinic. This work builds on that study and shows that there may be potential for developing an opt-in system for patients that could analyze their social media posts and provide extra information for clinicians to refine care delivery. Merchant said that it's tough to predict how widespread such a system would be, but it "could be valuable" for patients who use social media frequently.
Analysis of Facebook posts to determine depression is shifting the goal posts extraordinarily.
But i don't blame you. It's all you had.
um,
the doctors admit that using facebook posts picked it up 3 months earlier then their clinics did.
did you not read the article?
and are you telling me zuckerberg and his team of incredibly talented staff, combined with AI, combined with machine learning, combined with
Deep Text arent light years ahead of a few docs from pennsylvania
From facebooks own bragging speil
Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people's experiences with our products, whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam.
With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages.
DeepText leverages several deep neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. We use FbLearner Flow and Torch for model training. Trained models are served with a click of a button through the FBLearner Predictor platform, which provides a scalable and reliable model distribution infrastructure. Facebook engineers can easily build new DeepText models through the self-serve architecture that DeepText provides.