AI IN MEDICAL IMAGING: THE REVOLUTION?
Using MRI, researchers at IBM and the University of Alberta in Canada examined the brains of 95 patients and used the images to create a model of schizophrenia. Using that model, an artificial intelligence machine was able to distinguish between those with schizophrenia and the control group.
More so, after retrospective analysis, the AI technology also exemplified its ability to examine various brain regions and conclude the severity of the symptoms.
Speaking after the research, Ajay Royyuru, vice of healthcare and life sciences with IBM Research said:
“The ultimate goal of this research effort is to identify and develop objective, data-driven measures for characterising mental states, and apply them to psychiatric and neurological disorders. We also hope to offer new insights into how AI and machine learning can be used to analyse psychiatric and neurological disorders to aide psychiatrists in their assessment and treatment of patients.”
This news comes after much speculation on the role AI can and might play in the medical imaging industry. Machines such as the one used in this study offer a prime example of how AI and machine learning can significantly boost workflow efficiency, whilst also improving patient care.
However, one of the biggest problems that has prevented AI from being introduced unanimously across the medical imaging sector is the overload of patient information. Technology that could sift through this data is now a popular concept throughout the medical imaging industry.
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