Lung cancer is one of the malignant tumours with the highest morbidity and mortality rates worldwide today, posing a major threat to human health. Accurate diagnosis and standardised treatment play a crucial role in improving the survival rate of lung cancer patients. In recent years, the rapid rise of artificial intelligence (AI) has brought about significant changes in the medical field, providing a new diagnostic and treatment model for lung cancer, and making a series of breakthroughs in lung cancer diagnostic imaging, pathological diagnosis, surgical oncology, radiotherapy, and drug development and treatment. This article introduces the current status of AI application in the field of lung cancer diagnosis and treatment, and extensively discusses the current challenges and future prospects, hoping to provide references and suggestions for future clinical practice.

Lung cancer is one of the malignant tumours with the highest morbidity and mortality rates worldwide today, posing a major threat to human health. Accurate diagnosis and standardised treatment play a crucial role in improving the survival rate of lung cancer patients. In recent years, the rapid rise of artificial intelligence (AI) has brought about significant changes in the medical field, providing a new diagnostic and treatment model for lung cancer, and making a series of breakthroughs in lung cancer diagnostic imaging, pathological diagnosis, surgical oncology, radiotherapy, and drug development and treatment. This article introduces the current status of AI application in the field of lung cancer diagnosis and treatment, and extensively discusses the current challenges and future prospects, hoping to provide references and suggestions for future clinical practice.

Objective From the perspective of China's health system,evaluate the cost-effectiveness of furmonertinib compared to gefitinib in first-line monotherapy for EGFR mutation-positive advanced non-small cell lung cancer.Methods Based on the FURLONG study of phase Ⅲ clinical trials,a three-state partitioned survival model was constructed and combined with parameters such as treatment cost,utility value,the incidence of adverse reactions,and discount rate;the total incremental cost-effectiveness ratio(ICER)was simulated.Then,the ICER value was compared with the willingness to pay(WTP)value to determine the economic feasibility of furmonertinib compared to gefitinib as a first-line treatment for EGFR mutation-positive advanced non-small cell lung cancer.Results The basic analysis results show that the treatment group with furmonertinib incurred an additional cost of 85 786 yuan compared to the treatment group with gefitinib,but obtained an additional 0.62 QALYs,with an incremental cost-effectiveness ratio of 138 306 yuan,which is less than three times China's per capita GDP.One-way sensitivity analysis shows that the best support treatment cost,PFS utility value,and PD utility value significantly impact the ICER results.The results of probability sensitivity analysis show that when the WTP is three times China's per capita GDP,the probability of economic viability of the furmonertinib group compared to the gefitinib group is 100.0%.The scenario analysis results verified the robustness of the underlying analysis results.Conclusion Under the willingness to pay threshold of three times China's per capita GDP in 2022,Choosing furmonertinib as a first-line monotherapy for EGFR mutation-positive advanced non-small cell lung cancer is more cost-effective than gefitinib.