Expert consensus on lung cancer screening management empowered by GPT-LSapp 5A in primary hospitals
10.12025/j.issn.1008-6358.2025.20250867
- VernacularTitle:GPT-LSapp 5A赋能基层医院肺癌筛查管理专家共识
- Author:
Alliance Against Lung Cancer CHINESE
1
;
Engineer & Technology Research Center of Internet of Things for Respiratory Medicine SHANGHAI
1
;
Group on Lung Cancer Screening and Management in Primary Hospitals Empowered by the International Association of Metaverse in Medicine EXPERT
1
Author Information
1. .
- Publication Type:Standardandguideline
- Keywords:
generative pre-trained transformer;
Internet of Things;
natural language processing;
artificial intelligence;
lung cancer screening;
primary hospital
- From:
Chinese Journal of Clinical Medicine
2026;33(4):736-748
- CountryChina
- Language:Chinese
-
Abstract:
As the leading cause of cancer death worldwide, lung cancer sees about 2.1 million new cases and 1.8 million deaths every year, mainly caused by smoking, secondhand smoke and air pollution. Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) are the main types, which put a heavy burden on patients’ family. In order to reduce the burden of lung cancer patients, prevention and early screening are crucial, and the survival rate of patients with early-stage NSCLC can exceed 85%, but the lack of primary medical resources affects early detection and early treatment. To this end, professor Bai Chunxue’ team has developed the GPT-enabled Lung Cancer Screening 5A program (GPT-LSapp 5A) by combining generative pre-trained transformer (GPT) and Internet of Things (IoT) technologies. The program integrates chest CT, clinical information and laboratory data to provide personalized diagnosis and treatment plans through the cloud platform to alleviate the imbalance of medical resources. This technology can improve the efficiency of lung cancer screening in primary hospitals and achieve hierarchical diagnosis and treatment. GPT-LSapp 5A can integrate multi-source data to generate detailed screening reports, shorten the CT reading time, reduce the burden on doctors, and help upload case information, generate artificial intelligence (AI) reports, and remote consultation with experts to achieve resource sharing. Its “cloud” system is responsible for data integration and analysis, generating intelligent reports and diagnostic recommendations, and optimizing clinical pathways. The “end” program is responsible for data collection, preliminary analysis and user interaction at primary hospitals to improve the intelligence of the front-end. Although GPT-LSapp 5A faces challenges such as data privacy, format integration, and network performance, it can be solved through measures such as encryption, standardized interfaces, and edge computing. With the advancement of AI technology, GPT-LSapp 5A is expected to play a key role in lung cancer screening at primary hospitals, channeling medical resources down to the community level and improving patient outcomes.
