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Artificial intelligence could help in diagnosis of ADHD in adults

Source: Yorkshire Post as of 27-04-2020

UNIVERSITY ACADEMICS in Yorkshire has harnessed artificial intelligence to aid the diagnosis of attention deficit hyperactivity disorder (ADHD), which could result in major cost savings for the NHS. A globally renowned expert in artificial intelligence (AI) from the University of Huddersfield has produced innovative research to show how technology can be used to support the diagnosis of ADHD in adults. Professor Grigoris Antoniou, the project lead from the university, said the work started after the NHS wanted to speed up diagnosis as currently treatments are available, but the process can be slow. “There are long and growing waiting lists, as people wait to be diagnosed and treated, and this can result in adverse effects on their work, their social life and their family life,” he said. He added a reason for the lengthening waiting time due to a limited number of specialist clinicians able to do a full diagnosis. It has been estimated that 1.5 million UK adults have ADHD, leading to a wide range of difficulties, jeopardising careers and relationships. The Royal College of Psychiatrists has also said that people with the disorder were more likely to be “involved in criminal behaviour or become suicidal”.

Professor Antoniou has already used artificial intelligence to develop its potential to predict suicide risk in mental health patients. He has now continued his research in collaboration with the South West Yorkshire Partnership NHS Foundation Trust in order to show how the technology can be used to help diagnose ADHD in adults and aid further treatment if needed. As part of the research data routinely collected prior to ADHD diagnosis was fed into an AI algorithm. Three outcomes Professor Grigoris Antoniou, project lead at the University of Huddersfield. are the result: yes or no to further treatment or an unclear result that requires further assessment of the patient. Professor Antoniou explained the technology will be able to identify the clear-cut cases. “In many cases, the data itself more or less tells us whether it is a ‘yes’ or a ‘no’ for further treatment,” he said. The researchers say the project will result in better decision making.

Two AI technologies were used in the project – machine-learning using data from previous cases and trained a prediction model and knowledge-based, working with clinical experts and asking what their diagnosis would be if they are faced with this data. The technology is fully embedded in a clinical pathway which ensures there will always be a clinician who can over-ride the AI result. It could result in major cost savings for the NHS and Grow MedTech – a major UK programme providing specialist support for innovation in medical technologies has provided backing for the technology for future development. There are long and growing waiting lists, as people wait to be diagnosed.

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