https://scholars.lib.ntu.edu.tw/handle/123456789/624509
標題: | Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography | 作者: | Chen, Li-Wei SHUN-MAO YANG Chuang, Ching-Chia Wang, Hao-Jen Chen, Yi-Chang MONG-WEI LIN MIN-SHU HSIEH Antonoff, Mara B YEUN-CHUNG CHANG Wu, Carol C Pan, Tinsu CHUNG-MING CHEN |
關鍵字: | INTERNATIONAL-ASSOCIATION; IASLC/ATS/ERS CLASSIFICATION; PROGNOSTIC IMPACT; TUMOR RECURRENCE; CT; SUBTYPE; RESECTION; SURVIVAL; SIZE | 公開日期: | 十一月-2022 | 出版社: | SPRINGER | 卷: | 29 | 期: | 12 | 起(迄)頁: | 7473 | 來源出版物: | Annals of surgical oncology | 摘要: | High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation component masks with deep learning in the prediction of high-grade components to optimize surgical strategy preoperatively. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/624509 | ISSN: | 1068-9265 | DOI: | 10.1245/s10434-022-12055-5 |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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