Papers by Seongsu Bae
Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes (2024.findings-acl)
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Sunjun Kweon, Junu Kim, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, Jungwoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, Seungjin Baek, Chang Hoon Han, Yoon Bin Jung, Yohan Jo, Edward Choi
| Challenge: | Clinical notes are an extensive repository of information specific to individual patients. |
| Approach: | They create synthetic large-scale clinical notes using publicly available case reports extracted from biomedical literature and train a clinical large language model, Asclepius. |
| Outcome: | The proposed model outperforms several other models and is supported by detailed evaluations conducted by GPT-4 and medical professionals. |