Researchers developed a novel machine learning algorithm using extreme gradient boost to predict 1-, 5-, and 10-year mortality risk in patients with primary appendiceal cancer. The model exhibited high prediction accuracy, with a maximum area under the curve of 0.909 for the 10-year model. Variables such as disease grade, histology, lymph node involvement, and distant disease significantly influenced predictive ability. The model outperformed previous nomograms, incorporating a wide range of patient, surgical, and pathologic variables for improved prognosis prediction.
Journal Article by Winicki NM, Radomski SN (…) Greer JB et 3 al. in BMC Surg
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