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Effectively Integrating CNN and Low-Complexity Transformer for Lung Cancer Tumor Prediction After Neoadjuvant Chemoimmunotherapy

Jiancun Zhou Xianzhen Tan Hulin Kuang Jianxin Wang

大数据挖掘与分析（英文版）2025，Vol.8Issue(5)：981-996,16.

大数据挖掘与分析（英文版）2025，Vol.8Issue(5)：981-996,16.DOI:10.26599/BDMA.2024.9020088

Effectively Integrating CNN and Low-Complexity Transformer for Lung Cancer Tumor Prediction After Neoadjuvant Chemoimmunotherapy

Jiancun Zhou ¹Xianzhen Tan ²Hulin Kuang ²Jianxin Wang²

作者信息

1. Hunan Provincial Key Lab on Bioinformatics,School of Computer Science and Engineering,Central South University,Changsha 410083,China||College of Information and Electronic Engineering,Hunan City University,Yiyang 413000,China
2. Hunan Provincial Key Lab on Bioinformatics,School of Computer Science and Engineering,Central South University,Changsha 410083,China
折叠

摘要

关键词

lung cancer tumor prediction/neoadjuvant chemoimmunotherapy/hybrid convolutional neural network(CNN)and Transformer network/low-complexity self-attention

Key words

lung cancer tumor prediction/neoadjuvant chemoimmunotherapy/hybrid convolutional neural network(CNN)and Transformer network/low-complexity self-attention

引用本文复制引用

Jiancun Zhou,Xianzhen Tan,Hulin Kuang,Jianxin Wang..Effectively Integrating CNN and Low-Complexity Transformer for Lung Cancer Tumor Prediction After Neoadjuvant Chemoimmunotherapy[J].大数据挖掘与分析（英文版）,2025,8(5):981-996,16.

基金项目

This work was supported in part by the National Key Research and Development Program of China(No.2021YFF1201200),the Science and Technology Innovation Program of Hunan Province(No.2022RC1031),the Natural Science Foundation of Hunan Province(No.2023JJ50354),the Scientific Research Project of Hunan Education Department(No.24A0575),and the High Performance Computing Center of Central South University. （No.2021YFF1201200）

大数据挖掘与分析（英文版）

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