cientists have developed a new tool, based on AI language models, that could help to diagnose schizophrenia.
Researchers at University College London and Oxford University found that an automated analysis of language could help mental health doctors to diagnose and assess psychiatric conditions.
Schizophrenia is a debilitating and common psychiatric disorder that affects around 24 million people worldwide and over 685,000 people in the UK. Symptoms of the condition include hallucinations, delusions, confused thoughts and changes in behaviour.
Psychiatric diagnosis is based almost entirely on talking with patients and those close to them, with only a minimal role for tests such as blood tests and brain scans.
For the study, researchers asked 26 participants with schizophrenia and 26 control participants to complete two verbal fluency tasks. These involved participants being asked to name as many words as they could belonging to the category “animals”, or starting with the letter “p”, in five minutes.
To analyse the answers given by participants, the team used an AI language model that had been trained on vast amounts of internet text to represent the meaning of words in a similar way to humans.
They tested whether the words people spontaneously recalled could be predicted by the AI model, and whether this predictability was reduced in patients with schizophrenia.
Researchers found that the answers given by control participants were more predictable by the AI model than those generated by people with schizophrenia.
This difference was found to be largest in patients with the most severe symptoms.
Scientists believe that this difference could be due to the way the brain learns relationships between memories and ideas, which are stored in “cognitive maps”.
Previous studies have found that “cognitive mapping” is deficient in schizophrenia patients, who can struggle to express coherent thought. As a result, many patients can struggle to communicate.
Researchers found support for their theory in a second part of the same study where brain scanning was used to measure activity in parts of the brain involved in learning and storing these “cognitive maps”.
Lead author, Dr Matthew Nour, of the UCL Queen Square Institute of Neurology and University of Oxford, said: “Until very recently, the automatic analysis of language has been out of reach of doctors and scientists. However, with the advent of AI language models such as ChatGPT, this situation is changing.
“This work shows the potential of applying AI language models to psychiatry – a medical field intimately related to language and meaning.”
The team from UCL and Oxford plan to use the technology in a larger sample of patients to test whether it might prove useful in the clinic.
Dr Nour added: “We are entering a very exciting time in neuroscience and mental health research. By combining state-of-the-art AI language models and brain scanning technology, we are beginning to uncover how meaning is constructed in the brain, and how this might go awry in psychiatric disorders.
“There is enormous interest in using AI language models in medicine. If these tools prove safe and robust, I expect they will begin to be deployed in the clinic within the next decade.”
