Evaluating generative AI models for explainable pathological feature extraction in lung adenocarcinoma: grading assessment and prognostic model construction

GenAI models demonstrated significant potential in lung adenocarcinoma pathology, with Claude-3.5-Sonnet exhibiting superior performance in grading prediction and robust prognostic capabilities. These findings indicate promising applications of AI in lung adenocarcinoma diagnosis and clinical management.

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Publication Details

Journal
International Journal of Surgery
Published
2025-05-28
DOI
https://doi.org/10.1097/js9.0000000000002507
Citations
6
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
8.16
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article

Evaluating generative AI models for explainable pathological feature extraction in lung adenocarcinoma: grading assessment and prognostic model construction

Bufu Tang, Wenyi Gan, Quan Cheng, Dongqiang Zeng et al.
6 citations
International Journal of Surgery
Radiomics and Machine Learning in Medical Imaging
8.16
article

Evaluating generative AI models for explainable pathological feature extraction in lung adenocarcinoma: grading assessment and prognostic model construction

Bufu Tang, Wenyi Gan, Quan Cheng, Dongqiang Zeng, Zhenfa Zhang, Lingxuan Zhu, Suyin Feng, Hank Z. H. Wong, Yuying Feng, Peng Luo, Mingjia Xiao, Weiming Mou, Guangdi Chu, Aimin Jiang, Junyi Shen, Chunrong Dong, Anqi Lin, Shengkun Peng, Z. P. Xie, Jian Zhang, Qi Chang, Zaoqu Liu, Yifeng Bai
article en
6 citations

Abstract

GenAI models demonstrated significant potential in lung adenocarcinoma pathology, with Claude-3.5-Sonnet exhibiting superior performance in grading prediction and robust prognostic capabilities. These findings indicate promising applications of AI in lung adenocarcinoma diagnosis and clinical management.

International Journal of SurgeryVol. 111(7)
Qingdao University (CN), Jiangnan University (CN), Central South University (CN), University of Electronic Science and Technology of China (CN), Sun Yat-sen University (CN), Jinan University (CN), Chinese University of Hong Kong (HK), Second Military Medical University (CN), Shanghai Jiao Tong University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Fudan University (CN), Wenzhou Medical University (CN), Tianjin Medical University Cancer Institute and Hospital (CN), Quzhou City People's Hospital (CN), Sixth Affiliated Hospital of Sun Yat-sen University (CN), Nanfang Hospital (CN), Zhuhai People's Hospital (CN), Wuxi Fourth People's Hospital (CN), Affiliated Hospital of Qingdao University (CN), Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (CN), Zhujiang Hospital (CN), Zhongshan Hospital (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), County Hospital (GB), Shanghai First People's Hospital (CN), Xiangya Hospital Central South University (CN), Kangda College of Nanjing Medical University, Southern Medical University (CN), Nanjing Medical University (CN), University of Hong Kong (HK), South China University of Technology (CN)
Openalex Percentile: Top 2%
Radiomics and Machine Learning in Medical Imaging
8.16
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