Transfer learning–based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma

Abstract Background To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC). Methods Retrospective data from 516 LADC patients, encompassing preoperati...

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I tiakina i:

Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua:	Xiaonan Shao, Xinyu Ge, Jianxiong Gao, Rong Niu, Yunmei Shi, Xiaoliang Shao, Zhenxing Jiang, Renyuan Li, Yuetao Wang
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	BMC 2024-03-01
Rangatū:	BMC Medical Imaging
Ngā marau:	Lung adenocarcinoma Positron emission tomography/computed tomography Deep learning; radiomics Epidermal growth factor receptor
Urunga tuihono:	https://doi.org/10.1186/s12880-024-01232-5
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

Transfer learning–based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma

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