1 code implementation • 5 Jul 2023 • Viktor Schlegel, Hao Li, Yuping Wu, Anand Subramanian, Thanh-Tung Nguyen, Abhinav Ramesh Kashyap, Daniel Beck, Xiaojun Zeng, Riza Theresa Batista-Navarro, Stefan Winkler, Goran Nenadic
This paper describes PULSAR, our system submission at the ImageClef 2023 MediQA-Sum task on summarising patient-doctor dialogues into clinical records.
1 code implementation • 5 Jun 2023 • Hao Li, Yuping Wu, Viktor Schlegel, Riza Batista-Navarro, Thanh-Tung Nguyen, Abhinav Ramesh Kashyap, Xiaojun Zeng, Daniel Beck, Stefan Winkler, Goran Nenadic
Medical progress notes play a crucial role in documenting a patient's hospital journey, including his or her condition, treatment plan, and any updates for healthcare providers.
2 code implementations • 23 Oct 2022 • Samuel Belkadi, Lifeng Han, Yuping Wu, Goran Nenadic
The experimental outcomes show that 1) CRF layers improved all language models; 2) referring to BIO-strict span level evaluation using macro-average F1 score, although the fine-tuned LLMs achieved 0. 83+ scores, the TransformerCRF model trained from scratch achieved 0. 78+, demonstrating comparable performances with much lower cost - e. g. with 39. 80\% less training parameters; 3) referring to BIO-strict span-level evaluation using weighted-average F1 score, ClinicalBERT-CRF, BERT-CRF, and TransformerCRF exhibited lower score differences, with 97. 59\%/97. 44\%/96. 84\% respectively.
1 code implementation • 8 Oct 2022 • Yuping Wu, Ching-Hsun Tseng, Jiayu Shang, Shengzhong Mao, Goran Nenadic, Xiao-jun Zeng
To fill these gaps, this paper first conducts the comparison analysis of oracle summaries based on EDUs and sentences, which provides evidence from both theoretical and experimental perspectives to justify and quantify that EDUs make summaries with higher automatic evaluation scores than sentences.