Programming Chatbots Using Natural Language: Generating Cervical Spine MRI Impressions
The findings of this study suggest that LLMs can be a valuable tool in automating the generation of radiology impressions. Claude 2, in particular, exhibited promising results, indicating its potential for clinical implementation. However, the study also points to the necessity for further research, especially in optimizing model performance and evaluating real-world applicability.
Authors
- Ahmed Salah Ismail (ORCID: https://orcid.org/0000-0003-3515-2293)
- Ahmed Abdelmonem
- Oleksiy Melnyk (ORCID: https://orcid.org/0000-0003-4587-6543)
- Ramin Javan (ORCID: https://orcid.org/0000-0001-8939-2781)
- Mary Heekin
- Theodore Kim (ORCID: https://orcid.org/0000-0001-7745-5482)
- Farris Jaamour
Institutions
- Dartmouth–Hitchcock Medical Center (US)
- George Washington University (US)
- California Institute of Behavioral Neurosciences and Psychology (United States) (US)
Publication Details
- Journal
- Cureus
- Published
- 2024-09-14
- DOI
- https://doi.org/10.7759/cureus.69410
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.24