AI Analyzes Eye Movements to Assess Mental Health in Cancer Patients

Good mental health is essential, and emerging research indicates that AI could play a valuable role in diagnosing mental health issues, especially for individuals experiencing significant stress. Scientists have created a groundbreaking system combining deep learning algorithms with eye tracking technology to assess the mental health of cancer patients post-surgery. This innovative approach aims to identify patients who may be suffering from anxiety or depression, particularly in situations where a human assessment isn't feasible.

The system employs a convolutional neural network alongside long short-term memory algorithms to analyze the eye movements of patients wearing Tobii Pro 2 tracking glasses as they reflect on artwork. By using gaze and pupil position data, the AI can predict how likely a patient is to express concerns on established questionnaires assessing hope, anxiety, and mental well-being.

Initial results are promising, showcasing an accuracy rate between 93.8% and 95%, depending on the specific test conducted. However, it’s important to note that the study examined only 25 subjects, which is a limited sample size. Additional research is necessary to confirm the AI's reliability in identifying at-risk patients, and the researchers have acknowledged the need for “further validation.”

Moreover, the acceptance of such technology hinges on patients' comfort with having machines analyze their eye movements. While participants in the study were at ease with this, others might find it alarming.

If the accuracy is upheld in larger studies, the AI could significantly benefit the healthcare sector. It would enable patients to recover at home while still monitoring their mental health, allowing psychotherapists to concentrate on individuals displaying warning signs. Ultimately, this technology has the potential to enhance the accessibility and quality of mental health support for those who need it most.