Predicting therapy dropout in chronic pain management: a machine learning approach to cannabis treatment
Our findings highlight the potential of ML and pharmacogenetics to personalize cannabis-based therapies, improving adherence and enabling more precise management of chronic pain. This research paves the way for the development of tailored therapeutic strategies that maximize the benefits of medical cannabis while minimizing its side effects.
Authors
- Annalisa Santucci (ORCID: https://orcid.org/0000-0001-6976-9086)
- Anna Visibelli (ORCID: https://orcid.org/0000-0001-9281-034X)
- Bianca Roncaglia (ORCID: https://orcid.org/0009-0002-0009-4011)
- Paolo Fusar‐Poli (ORCID: https://orcid.org/0000-0003-3582-6788)
- Ottavia Spiga (ORCID: https://orcid.org/0000-0002-0263-7107)
- Rebecca Finetti (ORCID: https://orcid.org/0009-0000-6969-1493)
Institutions
- University of Siena (IT)
- Italian Society of Physiotherapy (IT)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-02-20
- DOI
- https://doi.org/10.3389/frai.2025.1557894
- Citations
- 1
- Primary Topic
- Cannabis and Cannabinoid Research
- Type
- article
- Field-Weighted Citation Impact
- 1.39