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Disruptive technologies improving diagnosis and treatment of schizophrenia

Disruptive technologies improving diagnosis and treatment of schizophrenia

30 October | 0 Comments | By Rachael

In the United States, an estimated 44.7 million adults (18.3 percent) suffer from a range of mental disorders, such as depression, bipolar disorder, anxiety disorders and schizophrenia, to name a few. Despite the growing magnitude of psychiatric illnesses, approximately 35 million (14.4 percent) adults in the age group 18 and above received mental health services in the past year. A large proportion of people suffering from depressive symptoms continue to remain out of the medical care system.

Though early identification and diagnosis paves the way for effective treatment with improved outcomes, there continues to be substantial barriers in achieving this. In the case of schizophrenia, the problem further heightens due to the unavailability of any physical or lab test to provide an accurate diagnosis.

Schizophrenia is a chronic mental disorder that affects a person’s thoughts, feelings and perceptions, with the hallmark symptom being psychosis (experiencing auditory hallucinations and delusions). Despite being a rare mental disorders compared to others, it can prove debilitating and disabling due to the loss of touch with reality. Usually, schizophrenia is diagnosed by ruling out many other conditions having similar symptoms, such as seizure disorders, metabolic disorders, thyroid dysfunction, brain tumor, substance use disorder (SUD), etc. This results in a significant delay in treatment and enhancement in suffering among patients.

In an endeavor to create tools capable of diagnosing schizophrenia, a number of scientists and experts are exploring the potential of advanced techniques like machine learning and artificial intelligence (AI). The integration of such techniques in the mainstream treatment has proven a blessing for the patients of schizophrenia. They have proven to be a promising tool by ensuring accuracy in the results.

Computational tools and objective analysis

Recently, IBM scientists and researchers at the University of Alberta and the IBM Alberta Center for Advanced Studies have collaboratively been able to successfully use AI and machine learning algorithms to predict the disease with a 74 percent accuracy.

Using predictive analysis and other computational tools, psychiatrists would have a tool to objectively assess the symptoms and treatment options.  Interestingly, this technology would enable physicians to predict the likelihood of the disease in patients who were yet to display the symptoms. Moreover, clinicians could theoretically determine the severity of the common symptoms of schizophrenia to measure the progression of the disease and the effectiveness of treatment.

A machine learning approach by using AI examines the millions of brain cortical links that can identify schizophrenia and predict the severity of symptoms with a high degree of accuracy. Such technologies, unlike human brain, work objectively through huge volumes of data using permutation and combination. They provide a deeper insight into humans and problems.

In a study, researchers used functional Magnetic Resonance Imaging (fMRI) to measure brain activity through changes in blood flow in 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 the one afflicted with schizophrenia. This study demonstrated that the machine learning algorithm was able to determine the patients suffering from schizophrenia through the data collected from multiple sites with 74 percent accuracy.

Such disruptive technologies are playing a pivotal role in addressing the challenges of such global problems.  By determining the key brain areas affected by schizophrenia and other mental disorders, such technologies can be further enhanced through advanced research and development to ensure a full-proof treatment.

Advanced tools making treatment effective

Disruptive technologies are both innovative and multidisciplinary in nature. Therefore, they provide new insights and improve the understanding of the disease that can improve treatment and scope of recovery. Such tools, by determining reliable neuroimaging markers, provide a better diagnostic and predictive tool for different types of disorder, especially mental disorders.

If you or your loved one is showing symptoms of any mental health disorder, contact the Arizona Mental Health Helpline to access the state-of-the-art mental health treatment centers in Arizona. Call 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.