Bridging the conversational gap in epilepsy: Using large language models to reveal insights into patient behavior and concerns from online discussions
LLM analysis of online epilepsy communities provides novel insights into patient concerns often overlooked in clinical settings. These findings may improve patient-provider communication, inform personalized interventions, and support the development of patient-reported outcome measures. Additionally, hazard models can help identify at-risk individuals, offering opportunities for early mental health interventions.
Authors
- Elad Yom‐Tov (ORCID: https://orcid.org/0000-0002-2380-4584)
- Uriel Fennig (ORCID: https://orcid.org/0000-0002-5102-7874)
- Marina Boxer
- Nitai Weinberg
- Keren Altman (ORCID: https://orcid.org/0000-0003-4417-4267)
- Nicola Maggio (ORCID: https://orcid.org/0000-0001-5041-2108)
- Shany Guly Gofrit (ORCID: https://orcid.org/0000-0001-6104-606X)
- Roni Loebenstein
- Johnatan Nissan (ORCID: https://orcid.org/0000-0003-0526-6820)
- Leehe Savitsky
Institutions
- Bar-Ilan University (IL)
- Tel Aviv University (IL)
- Technion – Israel Institute of Technology (IL)
- Sheba Medical Center (IL)
Publication Details
- Journal
- Epilepsia
- Published
- 2024-12-10
- DOI
- https://doi.org/10.1111/epi.18226
- Citations
- 3
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 1.93