They have developed a neural network that can estimate the mental health of patients by analyzing their eye movements.
A dynamic that aims to help cancer patients who are experiencing anxiety or depression. While this AI has yet to be widely tested, it already shows potential to help people in certain contexts.
Analyzing occult movements to measure mental health
As mentioned in the document that is shared in Nature, have developed machine learning algorithms to help people with cancer, who have to cope with episodes of anxiety or depression.
In addition to regular sessions with a therapist, this group of scientists propose to use the HE for the evaluation of the mental health of the patient using a simple dynamic to track their occult movements. Although they have not carried out massive tests, they mention that they have tested AI with two groups: cancer patients who are going through a post-operative period, and people who do not have this disease.
The test was simple. These groups were exposed to a number of works of art while wearing tracking glasses. Using this dynamic, the AI tracked a series of patterns manifested by users thanks to the analysis of their eye movements and different aspects of the pupil.
And based on the data they share, this study achieved a precision level of 93.81 to 95%. While it is an encouraging result for a first test, they are in the early stages, and they still have a long way to go to show the true potential of this AI.
Its creators consider the possibility of integrating this dynamic in apps for mental health monitoring, allowing professionals to carry out this monitoring from the patients’ homes. So it could become a practical tool, which can be complemented with traditional therapies, to detect patients at risk or to adequately accompany people suffering from depression in their cancer treatments.