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Correspondence to Author: Xinyuan Cui¹, Wanting Hao¹,Shenshen Cui², Yanlei Liu²,Ruokun Li^1,4, Daxiang Cui^2,3*, Fuhua Yan^1,4. 

1. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
2. Institute of Nano Biomedicine and Engineering, School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai JiaoTong university, Shanghai 200240, China.
3. Medical and Engineering Cross Research Institute, The First Affiliated Hospital, School of Medicine of Henan University, Kaifeng 475001, China.
4. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China; Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of M edicine, Shanghai200025, China.

DOI: 10.52338/tclc.2025.4508

Abstract:

Lung cancer is the first cause of cancer death worldwide. How to realize precise theranostics and management of Lung cancer has huge clinical demand. In past decade, artificial intelligence (AI), especially machine learning (ML) and deep learning (DL) are broadly used in medicine. Herein we focus on reviewing the main advances of ML and DL in diagnosis, treatment and prognosis of lung cancer. Besides, we summarize AI’s advantages, explore how AI assists theranostics of lung cancer by innovative AI algorithms, then we discussed the opportunities and challenges as well as the future directions in the clinical implementation of AI in lung cancer. Overall, AI integrated with multidisciplinary technology and data is a new development trend, its application in theranostics of lung cancer owns excellent clinical transformation value and prospect in near future.

Keywords: Artificial intelligence; Deep learning; algorithms; Lung cancer; Theranostics.

Citation:

Dr.Daxiang Cui, Advances And Prospect Of Artificial Intelligence In Theranostics Of Lung Cancer. The Clinical Lung Cancer 2025.