Publications by authors named "Xingming Shu"
Article Synopsis
- Colorectal cancer is a growing health concern, and patients face a significant risk of developing lower limb deep vein thrombosis (DVT) after surgery.
- The study aimed to create a machine learning model that predicts the likelihood of DVT in these patients to improve treatment and safety during recovery.
- By analyzing data from 429 colorectal cancer patients and using advanced techniques, researchers found that the XGBoost model was the most effective, boasting an impressive AUC of 0.996, indicating its strong predictive capabilities.
Gastric cancer (GC) is one of the most common malignant tumors in the digestive tract, and chemotherapy plays an irreplaceable role in the comprehensive treatment of GC. However, chemoresistance makes it difficult for patients with GC to benefit steadily from chemotherapy in the long term, which ultimately leads to tumor recurrence, metastasis, and patient death. Elucidating the detailed mechanism of chemoresistance in GC and identifying specific therapeutic targets will help to solve the difficult problem of chemoresistance and improve the prognosis of patients with GC.
View Article and Find Full Text PDF