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Friday, December 9, 2016

To identify depression in humans, it was possible for filters to photos


Scientists from Harvard and the universities of Vermont, introduced a rather unusual way of identifying clinical depression. To do this, offer to pay attention to the pictures that a person posts on his account Instagram. Thus, according to the researchers, depression can tell is not so much the photograph itself, how it is selected for the filters.


photo: ru.wikipedia.org

Filters help people who are using various services for lovers of photography, to change the color scheme of your picture, thereby giving it a particular mood. In their study, the experts decided to check whether it is possible for these filters to get an idea about the mental health of the account owner, and came to the conclusion that it is, in all probability actually possible.

Experts have prepared a special algorithm to analyze which colors are made one or the other photo, and the facial features of people caught in the frame and some other parts. Based on these data, the program determines whether the suffering a person from depression. After analyzing nearly 44 thousand of photos posted 166 different users, the algorithm was able to give an appropriate response to the truth in 70 percent cases that, according to the researchers, is a very good result.

The surest signs of clinical depression were blue-gray and black-and-white filters. However, scientists appeal to a wide audience not to overestimate nor the algorithm they have created or discovered with it trends. According to experts, at this stage, their method is not intended for use in clinical practice. However, to use it in order to early detect potentially emerging depression and time to resort to more proven methods of its confirmation, according to the developers, it is possible.

Recently, another group of scientists found that people who are trying to social networks not behave like in ordinary life, more prone to stress than those who like “duality” is not peculiar.

source

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