Towards automated phenotype definition extraction using large language models
Abstract Electronic phenotyping involves a detailed analysis of both structured and unstructured data, employing rule-based methods, machine learning, natural language processing, and hybrid approaches. Currently, the development of accurate phenotype definitions demands extensive literature reviews...
Saved in:
| Main Authors: | Ramya Tekumalla, Juan M. Banda |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2024-10-01
|
| Series: | Genomics & Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44342-024-00023-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rooted in and beyond interaction: A systematic review of interactive affordances of chatbots for language learning amidst the rise of large language models
by: Yunfei Du, et al.
Published: (2025-09-01) -
Large language models’ capabilities in responding to tuberculosis medical questions: testing ChatGPT, Gemini, and Copilot
by: Meisam Dastani, et al.
Published: (2025-05-01) -
LLMs in the Generation of Seismic Alert Communiqués
by: Oscar Peña-Cáceres, et al.
Published: (2025-05-01) -
Large language models in thyroid diseases: Opportunities and challenges
by: Yiwen Zhang, et al.
Published: (2025-06-01) -
Changes in attitudes toward meat consumption after chatting with a large language model
by: Neslihan Karakaş, et al.
Published: (2025-12-01)