Machine learning techniques can detect brain problems
Science : Machine learning techniques can detect brain problems
Scientists have developed machine learning techniques to identify problems related to the brain more accurately. Although depression patients can be accurately identified as the primary disease, patients with depression and mental illness rarely experience one symptom or the other. Mental illness patients with depression have symptoms that most often go towards the dimension of depression.
Paris Alexander, a researcher at Birmingham University, says, "Most patients have multiple problems with co-morbidity. Therefore, people with mental disorders also experience depressive symptoms." He says that this poses a big challenge for doctors to be prescribed treatment without identification and co-morbidity. According to research published in the journal Schizophrenia Bulletin, scientists used machine learning techniques to design more accurate models to identify both diseases. They used it to check patients with mixed symptoms.
The researchers tested the answers given in the questionnaire, detailed interviews and MRIs of 300 patients. The research was carried out at 7 European Research Centers from funds received through the European Union. They identified several small groups of patients who could be classified with mental illness without any symptoms of depression or depression without mental symptoms. Using the data, he explored machine learning models of 'pure' depression and pure 'mental illness'. Researchers then tried machine learning tricks on the models of both diseases. Scientists said that the aim of the research was to make a profile of every patient for a highly accurate disease and to check the identification of symptoms, how accurate it is.
Piyush Verma
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