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Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study
14
Zitationen
15
Autoren
2024
Jahr
Abstract
The proposed framework achieves notable improvements in both accuracy and efficiency. Its application in the domain of ophthalmology showcases its potential for knowledge organization and retrieval. We performed a trend analysis that enables researchers and clinicians to easily categorize and retrieve relevant papers, saving time and effort in literature review and information gathering as well as identification of emerging scientific trends within different disciplines. Moreover, the extendibility of the model to other scientific fields broadens its impact in facilitating research and trend analysis across diverse disciplines.
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Autoren
Institutionen
- University of Tennessee Health Science Center(US)
- IBM (United States)(US)
- IBM Research - Thomas J. Watson Research Center(US)
- Aristotle University of Thessaloniki(GR)
- East Tennessee State University(US)
- The California Eye Institute(US)
- Hamad Medical Corporation(QA)
- Columbia College(CA)
- Gazi University(TR)
- Prevent Blindness(US)
- University of Maryland, Baltimore(US)
- Weill Cornell Medical College in Qatar(QA)