https://www.selleckchem.com/pr....oducts/azaindole-1.h
The feature selection indicated the top five predictors were tumor size, imaging density, carcinoembryonic antigen (CEA), maximal standardized uptake value (SUVmax), and age. Conclusions By incorporating clinical characteristics and radiographical features, it is feasible to develop ML-based models for the preoperative prediction of LNM in early-T-stage NSCLC, and the RFC model performed best.Background We aimed to evaluate osteoporosis, bone mineral density, and fracture risk in irradiated patients by computerized tomography derive
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