all AI news
Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data
March 29, 2024, 4:48 a.m. | Shan Chen, Jack Gallifant, Marco Guevara, Yanjun Gao, Majid Afshar, Timothy Miller, Dmitriy Dligach, Danielle S. Bitterman
cs.CL updates on arXiv.org arxiv.org
Abstract: Generative models have been showing potential for producing data in mass. This study explores the enhancement of clinical natural language processing performance by utilizing synthetic data generated from advanced language models. Promising results show feasible applications in such a high-stakes domain.
abstract advanced applications arxiv clinical cs.cl data domain generated generative generative models improving language language model language models language processing natural natural language natural language processing nlp performance processing results show study synthetic synthetic data through type
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
AI Engineering Manager
@ M47 Labs | Barcelona, Catalunya [Cataluña], Spain