| Autor: |
Chun En Yau, Qihuang Xie, Ren Yi Jonas Ho, Chun Yi Yau, Elaine Guan, Dawn Yi Xin Lee, Xinyan Zhou, Gerald Gui Ren Sng, Joshua Yi Min Tung, Andrew Fu Wah Ho, Ryan Shea Ying Cong Tan, Daniel Yan Zheng Lim |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Annals, Academy of Medicine, Singapore, Vol 53, Iss 9, Pp 578-581 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2972-4066 |
| DOI: |
10.47102/annals-acadmedsg.202414 |
| Popis: |
The Eastern Cooperative Oncology Group (ECOG) is a commonly used performance status (PS) scale in oncology. It influences cancer treatment decisions and clinical trial recruitment. However, there can be significant inter-rater variability in ECOG-PS scoring, due to subjectivity in human scoring and innate cognitive biases.1,2 We propose that generative pretrained transformers (GPT), a foundational large language model (LLM), can accurately and reliably score ECOG-PS. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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