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Researchers build machine that detects symptoms of schizophrenia

Yusuff Moshood

Researchers at the University of Alberta, Canada, have developed a machine that can analyse brain scans and predict early symptoms of schizophrenia in relatives of patients.

The machine, according to the researchers, can help enhance the early diagnosis and treatment of schizophrenia.

Scientists say schizophrenia is a serious mental disorder in which people interpret reality abnormally. It may result in some combination of hallucinations, delusions, and extremely disordered thinking and behaviour that impairs daily functioning, and can be disabling.

It is usually treated with a combination of drugs, psychotherapy and brain stimulation.

In their study published by Science Daily, the researchers said the machine was a step forward in developing an artificial intelligence tool to predict schizophrenia by analyzing brain scans.

According to the report, the machine was used to analyse functional magnetic resonance images of 57 healthy first-degree relatives (siblings or children) of schizophrenia patients.

“It accurately identified the 14 individuals who scored highest on a self-reported schizotypal personality trait scale.

“Our evidence-based tool looks at the neural signature in the brain, with the potential to be more accurate than diagnosis by the subjective assessment of symptoms alone,” said lead study author, Sunil Kalmady Vasu, a senior machine learning specialist in the Faculty of Medicine and Dentistry.

First-degree relatives of patients, they said, have up to a 19 per cent risk of developing schizophrenia during their lifetime, compared with the general population risk of less than one per cent.

Vasu noted that the tool is designed to be a decision support tool and would not replace diagnosis by a psychiatrist.

He also pointed out that while having schizotypal personality traits may cause people to be more vulnerable to psychosis, it is not certain that they will develop full-blown schizophrenia.

“The goal is for the tool to help with early diagnosis, to study the disease process of schizophrenia and to help identify symptom clusters,” said Kalmady Vasu, who is also a member of the Alberta Machine Intelligence Institute.

The tool, dubbed EMPaSchiz (Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction), was previously used to predict a diagnosis of schizophrenia with 87 per cent accuracy by examining patient brain scans.

It was developed by a team of researchers from U of A and the National Institute of Mental Health and Neurosciences in India.

According to Kalmady Vasu, the next steps for the research is to test the tool’s accuracy on non-familial individuals with schizotypal traits and to track assessed individuals over time to learn whether they develop schizophrenia later in life.

The World Health Organisation says schizophrenia is a chronic and severe mental disorder affecting 20 million people worldwide.

Schizophrenia, WHO said, is characterized by distortions in thinking, perception, emotions, language, sense of self and behaviour. Common experiences include hallucinations (hearing voices or seeing things that are not there) and delusions (fixed, false beliefs).

“Worldwide, schizophrenia is associated with considerable disability and may affect educational and occupational performance.

People with schizophrenia are 2-3 times more likely to die early than the general population. This is often due to preventable physical diseases, such as cardiovascular disease, metabolic disease and infections,” WHO said.

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