Abstract
We introduce OlloBot, an Arabic conversational agent that assists physicians and supports patients with the care process. It doesn’t replace the physicians, instead provides health tracking and support and assists physicians with the care delivery through a conversation medium. The current model comprises healthy diet, physical activity, mental health, in addition to food logging. Not only OlloBot tracks user daily food, it also offers useful tips for healthier living. We will discuss the design, development and testing of OlloBot, and highlight the findings and limitations arose from the testing.- Anthology ID:
- R19-1034
- Volume:
- Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
- Month:
- September
- Year:
- 2019
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 295–303
- Language:
- URL:
- https://aclanthology.org/R19-1034
- DOI:
- 10.26615/978-954-452-056-4_034
- Cite (ACL):
- Ahmed Fadhil and Ahmed AbuRa’ed. 2019. OlloBot - Towards A Text-Based Arabic Health Conversational Agent: Evaluation and Results. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 295–303, Varna, Bulgaria. INCOMA Ltd..
- Cite (Informal):
- OlloBot - Towards A Text-Based Arabic Health Conversational Agent: Evaluation and Results (Fadhil & AbuRa’ed, RANLP 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/R19-1034.pdf