https://www.selleckchem.com/products/dt-061-smap.html 14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model 69.95 vs. 24.80months, p < 0.001; 3D-CNN Model 64.06 vs. 31.05months, p = 0.027). The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation. The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation. To evaluate the efficacy and safety of an immune checkpoint inhibitor (ICI) combined with chemotherapy in patients with advanced SCLC. We searched published randomized-controlled trials (RCTs) to compare the effect of ICIs combined with chemotherapy and chemotherapy alone on SCLC. The extracted data included the number of people who achieved an objective response rate (ORR), the disease control rate (DCR), the hazard ratio (HR) of progression-free survival (PFS), and the overall survival (OS) with 95% confidence intervals (95% CI). Six RCTs involving 2477 patients were included. Compared with chemotherapy alone, patients receiving an ICI combined with chemotherapy had a significantly longer PFS (HR, 0.91; 95% CI 0.88-0.95, p < 0.00001) and OS (HR 0.92; 95% CI 0.89-0.96, p = 0.0001). The ORR increased, but the difference was not statistically significant (RR 1.05; 95% CI 0.99-1.12, p = 0.13). There was no significant difference in the DCR between the two treatment regimens; however, in patients treated with an ICI, fatigue, rashes, diarrhea, and elevat