Non-small cell lung cancer is the main cause of cancer death in the world, and its incidence is increasing year by year, seriously endangering human health. Early non-small cell lung cancer is generally difficult to be detected based on symptoms and signs. Therefore, accurate pathological diagnosis and accurate prediction of prognosis are crucial for formulating the best treatment plan for non-small cell lung cancer patients and improving their survival. The application of artificial intelligence in the diagnosis and treatment of non-small cell lung cancer has shown good performance and great potential effect. This paper introduces the research progress of artificial intelligence in predicting the classification, staging, genomics and prognosis of non-small cell lung cancer.
ObjectiveTo investigate the clinical effect of three-port Da Vinci robot-assisted radical resection of lung cancer. MethodsThe clinical data of patients who underwent Da Vinci robot-assisted radical resection of lung cancer in the Second Department of Thoracic Surgery, the First Affiliated Hospital of Xiamen University from April 2021 to March 2022 were retrospectively analyzed. According to the number of surgical ports, they were divided into two groups: a three-port group (three-port Da Vinci robot-assisted radical resection of lung cancer), and a four-port group (traditional Da Vinci robot-assisted radical resection of lung cancer). The operation time, intraoperative bleeding, lymphadenectomy, total thoracic drainage, extubation time, postoperative complications and postoperative pain of the two groups were compared and analyzed. ResultsA total of 58 patients were included, including 19 males and 39 females, aged 31-79 years. There were 21 patients in the three-port group, and 37 patients in the four-port group. The visual analogue scores on the first and third day after the operation were 4.33±1.20 points and 2.24±0.77 points in the three-port group, and 5.11±1.22 points and 2.78±1.06 points in the four-port group, and there were statistical differences between the two groups (P<0.05). There was no significant difference between the two groups in terms of operation time, intraoperative bleeding, lymph node dissection, postoperative thoracic drainage, time of thoracic tube insertion or postoperative complications (P>0.05). ConclusionThree-port Da Vinci robot-assisted radical resection of lung cancer can reduce the postoperative pain without increasing the operation difficulty and complications, and can be widely used in the clinical practice.