Grassi2021 - Prediction of illness remission in patients with Obsessive-Compulsive Disorder with supervised machine learning §

• Type:#article
• Year read:#read2021
• Subject: OCD prediction machine learning
• Bibtex: @grassi2021
• Bibliography: Grassi, M., Rickelt, J., Caldirola, D., Eikelenboom, M., van Oppen, P., Dumontier, M., Perna, G., & Schruers, K. (2022). Prediction of illness remission in patients with Obsessive-Compulsive Disorder with supervised machine learning. Journal of Affective Disorders, 296, 117–125. https://doi.org/10.1016/j.jad.2021.09.042

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Example citation §

Machine learning techniques have been used to predict the two-year remission status of patients with OCD, yielding a balanced accuracy of 72% in test data [@grassi2021].

Key takeaways §

• Gradient boosted decision trees (XGBoost in R)
• n = 287, AUROC 0.78 (sens 73% spec 71%)
• Small test data sites and large variations between sites.

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