Researchers use AI to predict antidepressant outcomes in youth

Journal of Psychology and Psychiatry (2022). DOI: 10.1111 / jcpp.13580 “width =” 800 “height =” 530 “/>

Figure 1. (A) The use of a table-based vision tool designed to predict treatment outcomes in children and adolescents treated with fluoxetine or duloxetine. (B) Statistical Evaluation Scale (CDRS-R) Total score in fluoxetine-treated patients. (C) Engine learning speed. Credit: Journal of Professional Psychologists. (2022). DOI: 10.1111 / jcpp.13580

Researchers at the Mayo Clinic have taken the first step of using artificial intelligence (AI) to predict early outcomes with antidepressant treatment in children and adolescents with dementia, in a published study Journal of Professional Psychologists.. This project originated from a collaborative effort between the departments of Molecular Pharmacology and Experimental Therapeutics, and Psychiatry and Psychology, at Mayo Clinic, with support from Mayo Clinic’s Center for Individualized Medicine.

“This initial work demonstrates that AI is committed to helping clinical decisions by informing physicians about the choice, use and treatment of antidepressants for children and adolescents with great inconvenience“says Paul Croarkin, DO, Mayo Clinic psychiatrist and lead author of the study.

In the study, the researchers found differences in the six depressive symptoms: difficulty having fun, withdrawing, excessive tiredness, sadness, lack of pride and depression.

They assessed these signs with Review of Children’s Depression Assessment to predict the effect up to 10 to 12 weeks of antidepressant pharmacotherapy:

  • Six signs predicted results for 10 to 12 weeks in four to six weeks in fluoxetine test data, with an average accuracy of 73%.
  • Six identical symptoms predicted 10 to 12 weeks effect in four to six weeks in duloxetine test data, with an average accuracy of 76%.
  • In placebo-treated patients, the prognosis and remission rate were significantly lower than that of antidepressants at 67%.

These results indicate the potential of AI as well patient data to ensure children and adolescents receive treatment that has the highest potential to deliver therapeutic benefits with minimal side effects, says Arjun Athreya, Ph.D., Mayo Clinic researcher and lead author of the study.

“We have designed the algorithm to simulate the clinician’s perception of treatment at an interim basis based on their estimate of whether the patient will benefit from a combination therapy at the current rate,” she said. Dr. Athreya. “Therefore, it is important for me as a computer engineer to integrate and maintain the operation carefully to not only understand the patient’s needs, but also how AI can be used clinically for the benefit of the patient.”

Next steps

The findings are the basis for future work that includes physiological data, brain-based measures and therapeutic data for improved treatment options for young people with depression. This will improve the care of young patients with depression, and help physicians initiate and use antibiotics in the most vulnerable patients.

“Technological advances have been made in tools that can improve treatment methods,” said Liewei Wang, MD, Ph.D., Bernard and Edith Waterman Director of Pharmacogenomics Program and Director of the Center for Drugs at Mayo Clinic. “Predicting the outcome a children and young people being cared for for depression are critical in controlling what could be the burden of long-term illnesses. ”

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Learn more:
Arjun P. Athreya et al, Evidence for machine learning led to the vision and location of serious consequences in the care of depressed children with antidepressants, Journal of Professional Psychologists. (2022). DOI: 10.1111 / jcpp.13580

hint: Researchers are using AI to predict antidepressant effects in adolescents (2022, March 22) retrieved March 22, 2022 from html

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