The goal of this observational study is to learn about the risk factors and prediction of postoperative venous thromboembolism (VTE) in patients undergoing lung cancer surgery. The main question it aims to answer is:

Which clinical, surgical, and laboratory factors are associated with the development of postoperative deep vein thrombosis (DVT) in lung cancer surgery patients, and can machine learning models accurately predict individual risk?

Participants undergoing lung cancer surgery will be prospectively followed for 30 days after surgery. Perioperative clinical data, laboratory results, and imaging findings will be collected to identify VTE risk factors and to develop a predictive model.

Inclusion Criteria:

1. Age ≥ 18 years
2. Patients undergoing surgical resection for lung cancer
3. Postoperative hospital stay ≥ 48 hours
4. Availability of perioperative clinical, laboratory, and imaging data
5. Willingness to provide informed consent and participate in 30-day follow-up

Exclusion Criteria:

1. Pre-existing deep vein thrombosis (DVT) or pulmonary embolism (PE) before surgery
2. Preoperative or ongoing anticoagulation therapy for ≥ 2 weeks
3. Severe coagulation disorders or bleeding diseases
4. Severe hepatic, renal, or hematologic dysfunction, or uncontrolled systemic infection
5. Concurrent major organ surgery (e.g., cardiac, liver surgery)
6. Pregnancy or lactation
7. Incomplete postoperative follow-up data

The study population consists of adult patients undergoing surgical resection for lung cancer at the Department of Thoracic Surgery, First Hospital of Jilin University. Participants will be prospectively followed for 30 days postoperatively to assess the occurrence of deep vein thrombosis (DVT) and to identify perioperative risk factors. All patients meeting inclusion criteria and without exclusion criteria will be eligible.