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Scientists device method to integrate machine learning with artificial intelligence to predict schizophrenia

Scientists device method to integrate machine learning with artificial intelligence to predict schizophrenia

27 December | 0 Comments | By Arizona Mental Health Helpline Team

In the United States, approximately 43.4 million adults (17.9 percent) suffered from a range of mental health conditions, such as depression, bipolar disorder, anxiety disorders, schizophrenia, etc., in 2015. Despite such a large proportion of the population suffering from mental illness, treatment is not sought so readily. Out of 16.2 million adults with any major depression episode, only 10.6 million adults received treatment in 2016.

Although early identification and diagnosis pave the way for effective treatment with improved outcomes, there continues to be substantial barriers in achieving this. In the case of schizophrenia, this is a major hurdle due to the lack of provisions for physical or lab test to diagnose the disease. Schizophrenia is a brain disorder that affects a person’s thoughts, feelings and perceptions, with the hallmark symptom being psychosis (experiencing auditory hallucinations and delusions).

Diagnosis of schizophrenia is usually done by ruling out many other conditions having similar symptoms, such as seizure disorders, metabolic disorders, thyroid dysfunction, brain tumor, drug abuse, etc. This significantly delays the treatment. With the advancements in science and technology, medical practitioners can now diagnose mental disorders by objectively assessing the patients.

Analysis will help psychiatrists objectively assess symptoms

As a part of an innovative collaboration, IBM scientists and researchers at the University of Alberta and the IBM Alberta Center for Advanced Studies have been able to leverage the advantages of disruptive technologies, such as artificial intelligence (AI) and machine learning algorithms, to predict diseases like schizophrenia with a 74 percent accuracy.

By using predictive computer analysis, psychiatrists will be able to objectively assess symptoms and treatment options. This technology could enable physicians to predict the likelihood of the disease in patients who were yet to display the symptoms. Thus, clinicians could theoretically determine the severity of the common symptoms of the disease to measure the progression path and the effectiveness of treatment.

Considering the high accuracy levels of computers in comparison to humans, a machine learning approach by using AI to examine the millions of brain cortical links can identify schizophrenia and predict the severity of symptoms. Unlike humans, computers can work objectively through the huge volumes of data and consider a number of permutations and combinations at once. This will provide a deeper insight into the patients’ mental condition. As a result, clinicians will have better evidence based on which they can take their decisions. Moreover, machine learning can help people to understand the complex systems like the human brain.

Computational psychiatry provides evidence-based model to identify schizophrenia

In the above program, researchers used functional magnetic resonance imaging (fMRI) to measure brain activity by analyzing the changes in blood flow or between the specific areas of the brain. They analyzed the scans of 95 participants and used machine learning techniques to develop a model of a brain closely resembling that afflicted with schizophrenia.

This evidence-based model was used for predicting the chances of schizophrenia in a yet to be seen patients by objectively examining the common symptoms, such as poor attention, lack of motivation, bizarre thoughts and behaviors, etc.

The program demonstrated that machine-learning algorithm can discriminate between patients with schizophrenia from those in the control group with 74 percent accuracy by determining the similarities in the brain activity in different areas of the brain.

Integrating technology to treat mental disorders

Such a unique and multidisciplinary approach is both innovative and effective. It provides new insights and improves the understanding of the neurobiology of diseases like schizophrenia. A few significant abnormal brain connections were also discovered during the research that can be incorporated in the future studies.

If you or your loved one is exhibiting symptoms of any mental disorder, contact the Arizona Mental Health Helpline to access information on the mental health treatment centers in Arizona where qualified medical representatives can decide on a treatment plan that best suits your needs. Call at our 24/7 helpline number 866-606-7791 or chat with our representatives to know more about the mental health disorder treatment centers in Arizona.


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