Machine learning prediction will be part of future treatment of depression
| Autor: | Matthew J Lennon, Catherine Harmer |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Australian & New Zealand Journal of Psychiatry. :000486742311582 |
| ISSN: | 1440-1614 0004-8674 |
| DOI: | 10.1177/00048674231158267 |
| Popis: | Machine learning (ML) is changing the way that medicine is practiced. While already clinically utilised in diagnostic radiology and outcome prediction in intensive care unit, ML approaches in psychiatry remain nascent. Implementing ML algorithms in psychiatry, particularly in the treatment of depression, is significantly more challenging than other areas of medicine in part because of the less demarcated disease nosology and greater variability in practice. Given the current exiguous capacity of clinicians to predict patient and treatment outcomes in depression, there is a significantly greater need for better predictive capability. Early studies have shown promising results. ML predictions were significantly better than chance within the sequenced treatment alternatives to relieve depression (STAR*D) trial (accuracy 64.6%, p |
| Databáze: | OpenAIRE |
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