Fatema Yasmin, Senior HR Manager, Uttara Crescent Hospital and Former Lecturer, South East University highlights the role of Artificial Intelligence (AI) in managing schizophrenia
Diagnosis of schizophrenia which has always been based on talk therapy, is now for the first time seeing hope for psychologists all around the world with the invention of the AI language model. AI language models are developed by UCL Queen Square Institute for Neurology which will act as revolutionary tools in the diagnosis of schizophrenia.
As we know schizophrenia is a serious mental health disorder impacting around 24 million individuals worldwide, which puts the affected individuals into challenges every day and impacts society as a whole. Schizophrenia affects 1 in 100 individuals over their lifetimes and causes them to present symptoms such as auditory hallucinations, delusions, paranoia, and social withdrawal. To get better treatment early detection is essential as the duration of symptoms before receiving treatment increases it can significantly impact the long-term impact of the treatment.
The fact is according to psychologists’ research, people dealing with schizophrenia gradually confront deteriorating health from mental illness to physical sicknesses and eventually increase the risk of premature death. Moreover, the widespread stigma associated with this disease fosters social isolation, prejudiced practices, and controlled entry to crucial services like healthcare, education, housing, and employment.
The cause of schizophrenia is unknown and complicated, encompassing a blend of genetic and environmental factors, along with psychosocial components. Intense cannabis consumption has also been associated with an increased likelihood of developing this disorder. Despite having viable treatment present only a few number of patient is getting access to this treatment. The majority number of patients remain untreated or undiagnosed.
In a significant advancement of science, researchers recently developed a revolutionary invention to diagnose schizophrenia by using the widely used term AI. Nowadays psychiatric diagnosis of schizophrenia heavily relies on discussions with patients and their close associates, with minimal involvement of diagnostic tests such as blood tests and brain scans. However, it lacks precision and hampers a deeper understanding of the effectiveness of treatments. Recently the researchers of the UCL Queen Square Institute for Neurology have invented an innovative approach named AI Language Model in the diagnosis and monitoring of psychiatric conditions.
As reported in the journal PNAS, Vol. 120 | No. 14 researchers discovered that individuals with schizophrenia exhibit subtle yet significant differences in their speech that correspond to the severity of their symptoms. They utilised brain scanning technology to establish connections between these linguistic variations and patterns of brain activity associated with how the brain organises relationships between memories and meanings.
Human cognitive processes rely on structured internal representations that encode relationships between entities in the world, often referred to as cognitive maps. A cognitive map is the mental representation of a person that serves an individual to acquire, code, store, recall, and decode information about the relative locations and attributes of phenomena in their everyday environment.
Clinical symptoms of schizophrenia, are associated with positive symptoms like thought disorders, delusions, and hallucinations, Negative symptoms like Social Withdrawal, Anhedonia, Reduced Motivation, and Cognitive Symptoms like Impaired Memory, Attention Difficulties, and Executive Function Impairment. Schizophrenia is also linked to abnormalities in neural processes supporting cognitive map representations.
In their findings, the researchers present a computational analysis of semantically guided conceptual sampling. They utilised this approach to test the hypothesis that individuals with schizophrenia exhibit in their speech. The researchers suggest that AI language models possess a distinctive capacity to identify subtle linguistic patterns that may indicate the presence of schizophrenia. Their emphasis centered on unraveling the processes by which the brain establishes and retains connections between memories and ideas.
The researchers use brain scans to assess activity in brain regions linked to the creation and storage of these cognitive maps.
For diagnosing schizophrenia. Top of researchers, employ mathematical models to identify how their brains process and retrieve information from distinct speech patterns. In this manner of analysis, affected individuals conveyed information differed significantly from those without having any health issues, indicating potential challenges in how their brains process and retrieve information. The incorporation of AI into the diagnostic process aims to address the gap in identifying psychotic conditions and providing timely medical intervention.
However, ethical considerations arise regarding the utilization of AI in mental health diagnosis. Concerning questions arise about the potential biases related to gender and ethnicity. Despite these fears, researchers emphasize the importance of bridging the gap between traditional diagnostic approaches and the potential advantages offered by AI.
As AI continues to advance, the incorporation of these tools holds hope for achieving earlier and more accurate diagnoses of schizophrenia, ultimately improving the lives of the millions affected by this challenging mental health condition. In recent years, AI has also been used to find drugs for schizophrenia, by using Smart Cube which is an automated testing platform that employs machine learning to process millions of data collected to identify potential drugs for schizophrenia. After decades of working with AI researchers are bringing several treatments to clinical trials which set out to treat schizophrenia.
Managing schizophrenia is an ongoing process as it currently lacks a cure. However, symptoms can often be effectively managed through a combination of medication and therapy. Often, multiple methods are necessary for comprehensive treatment, including antipsychotic medicines, therapy, training, and participation in self-help and support groups. Early treatment and access to supportive services play a crucial role in enabling affected individuals to lead productive lives.
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