可读性
医学
神经外科
变压器
医学物理学
外科
语言学
量子力学
物理
哲学
电压
作者
Raj Swaroop Lavadi,Ben Carnovale,Zayaan Tirmizi,Avi A. Gajjar,Rohit Prem Kumar,Manan Shah,D. Kojo Hamilton,Nitin Agarwal
标识
DOI:10.1016/j.wneu.2024.11.052
摘要
AtlasGPT represents an innovative generative pre-trained transformer (GPT), trained using neurosurgery literature. Its ability to contour its response according to the training level of the user is unique; however, whether its responses can be comprehended at each user's training level remains unknown. This study aimed to analyze the readability of responses provided by AtlasGPT.
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