Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Fu Yujuan"'
Large language models (LLMs) have demonstrated great performance across various benchmarks, showing potential as general-purpose task solvers. However, as LLMs are typically trained on vast amounts of data, a significant concern in their evaluation i
Externí odkaz:
http://arxiv.org/abs/2410.18966
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning
Autor:
Fu, Yujuan Velvin, Ramachandran, Giridhar Kaushik, Park, Namu, Lybarger, Kevin, Xia, Fei, Uzuner, Ozlem, Yetisgen, Meliha
Large language models (LLMs) such as ChatGPT are fine-tuned on large and diverse instruction-following corpora, and can generalize to new tasks. However, those instruction-tuned LLMs often perform poorly in specialized medical natural language unders
Externí odkaz:
http://arxiv.org/abs/2410.18955
Autor:
Fu, Yujuan, Ramachandran, Giridhar Kaushik, Halwani, Ahmad, McInnes, Bridget T., Xia, Fei, Lybarger, Kevin, Yetisgen, Meliha, Uzuner, Özlem
Publikováno v:
Journal of the American Medical Informatics Association (2024): ocae231
Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symptom burden, we extrac
Externí odkaz:
http://arxiv.org/abs/2409.03905
Autor:
Fu, Yujuan, Ramachandran, Giridhar Kaushik, Dobbins, Nicholas J, Park, Namu, Leu, Michael, Rosenberg, Abby R., Lybarger, Kevin, Xia, Fei, Uzuner, Ozlem, Yetisgen, Meliha
Social determinants of health (SDoH) play a critical role in shaping health outcomes, particularly in pediatric populations where interventions can have long-term implications. SDoH are frequently studied in the Electronic Health Record (EHR), which
Externí odkaz:
http://arxiv.org/abs/2404.00826
Autor:
Ramachandran, Giridhar Kaushik, Fu, Yujuan, Han, Bin, Lybarger, Kevin, Dobbins, Nicholas J, Uzuner, Özlem, Yetisgen, Meliha
Social determinants of health (SDOH) documented in the electronic health record through unstructured text are increasingly being studied to understand how SDOH impacts patient health outcomes. In this work, we utilize the Social History Annotation Co
Externí odkaz:
http://arxiv.org/abs/2306.07170
Recent immense breakthroughs in generative models such as in GPT4 have precipitated re-imagined ubiquitous usage of these models in all applications. One area that can benefit by improvements in artificial intelligence (AI) is healthcare. The note ge
Externí odkaz:
http://arxiv.org/abs/2306.02022
Publikováno v:
In Heliyon 15 August 2024 10(15)
Publikováno v:
In Developmental Cell 17 June 2024 59(12):1538-1552
Publikováno v:
In Heliyon 29 February 2024 10(4)
Autor:
Zhao, Huiting, Shi, Chaowen, Han, Wei, Luo, Guanfa, Huang, Yumeng, Fu, Yujuan, Lu, Wen, Hu, Qingang, Shang, Zhengjun, Yang, Xihu
Publikováno v:
In Neoplasia January 2024 47