Automatic Personalized Impression Generation for PET Reports Using Large Language Models

PURPOSE: To determine if fine-tuned large language models (LLMs) can generate accurate, personalized impressions for whole-body PET reports. MATERIALS AND METHODS: Twelve language models were trained on a corpus of PET reports using the teacher-forcing algorithm, with the report findings as input an...

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Detalles Bibliográficos
Autores principales: Tie, Xin, Shin, Muheon, Pirasteh, Ali, Ibrahim, Nevein, Huemann, Zachary, Castellino, Sharon M., Kelly, Kara M., Garrett, John, Hu, Junjie, Cho, Steve Y., Bradshaw, Tyler J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614982/
https://www.ncbi.nlm.nih.gov/pubmed/37904738

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614982/
https://www.ncbi.nlm.nih.gov/pubmed/37904738

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