Depression is a disorder that seems simple, but its origins are complex and we still do not understand them at all. But machine learning can help scientists discover some of their mysteries to provide better treatments. For example, being down, feeling unhappy and not enjoying life, can produce acute personal dissatisfaction, but can also cause a dry mouth, which adds to the lack of interest of the person to improve their appearance and neglects their oral hygiene , which triggers the appearance of diseases you can go with your dentist in Tijuana for a good oral treatment

A patient must present several symptoms from a long list to be diagnosed with a severe depressive disorder, which is thought to be caused by a combination of genetic, environmental, and psychological factors. Once diagnosed, they can receive cognitive-behavioral therapies or drugs to improve their condition. But the treatments do not work the same for each patient since the symptoms can vary widely.

Recently, many artificial intelligence researchers have begun to develop machine learning techniques to explain medical disorders. Such approaches are able to detect trends and details in massive data sets that humans could never find. This allows us to offer results that can be used to diagnose other patients. The New Yorker recently published an especially interesting essay on the use of the technique to make diagnoses from medical images.

And there are similar ongoing jobs focused on depression. A study published this year in the journal Psychiatry Research showed that machine learning can analyze magnetic resonance imaging to determine the likelihood of someone suffering from the disorder.

And what is even more interesting is that, as Vox reports, researchers at the  are using a similar tactic to identify different types of depression. By using machine learning algorithms to scrutinize data captured when the brain is at rest, scientists have been able to categorize four different subtypes of the disorder that manifest as different combinations of anxiety and lack of pleasure.

Of course, not all projects to make accurate diagnoses using magnetic resonance imaging have been successful. But the artificial intelligence does seem to improve the chances of finding symptoms of the disease in the images that the doctors themselves. At the very least, the experiments reinforce the idea that there are different types of depression.

The focus of the images could be only a small part of a larger effort for machine learning to find clues to the disorder. For example, are using artificial intelligence to differentiate specific vocal patterns in people suffering from depression, as well as problems such as post-traumatic stress disorder.