A network-guided cross-cohort framework combining machine learning and co-expression analysis prioritized compact plasma protein signatures across 23 human diseases, matching ...
A multicenter study demonstrates that combining clinical variables with CT radiomics features enables machine learning models to accurately distinguish peripheral ...
A multicenter retrospective study of 96 Ewing sarcoma patients found that MRI radiomics models moderately outperformed expert radiological readings in ...
Researchers developed and temporally validated a preoperative nomogram combining body roundness index, pericholecystic fluid, and fibrinogen to predict difficult laparoscopic ...
An artificial neural network accurately predicted lymph node metastasis in prostate cancer patients undergoing radical prostatectomy, achieving 94.1 percent test ...
