Hepatic alveolar echinococcosis (HAE) and liver cancer had similaritiesin imaging results, clinical characteristics, and so on. And it is difficult forclinicians to distinguish them before operation. The aim of our study was to build adifferential diagnosis nomogram based on platelet (PLT) score model and use internalvalidation to check the model. The predicting model was constructed by theretrospective database that included in 153 patients with HAE (66 cases) or livercancer (87 cases), and all cases was confirmed by clinicopathology and collectedfrom November 2011 to December 2018. Lasso regression analysis model was used toconstruct data dimensionality reduction, elements selection, and building predictionmodel based on the 9 PLT-based scores. A multi-factor regression analysis wasperformed to construct a simplified prediction model, and we added the selectedPLT-based scores and relevant clinicopathologic features into the nomogram.Identification capability, calibration, and clinical serviceability of thesimplified model were evaluated by the Harrell’s concordance index (C-index),calibration plot, receiver operating characteristic curve (ROC), and decision curve.An internal validation was also evaluated by the bootstrap resampling. Thesimplified model, including in 4 selected factors, was significantly associated withdifferential diagnosis of HAE and liver cancer. Predictors of the simplifieddiagnosis nomogram consisted of the API index, the FIB-4 index, fibro-quotent(FibroQ), and fibrosis index constructed by King’s College Hospital (King’s score).The model presented a perfect identification capability, with a high C-index of0.929 (0.919 through internal validation), and good calibration. The area under thecurve (AUC) values of this simplified prediction nomogram was 0.929, and the resultof ROC indicated that this nomogram had a good predictive value. Decision curveanalysis showed that our differential diagnosis nomogram had clinicallyidentification capability. In conclusion, the differential diagnosis nomogram couldbe feasibly performed to verify the preoperative individualized diagnosis of HAE andliver cancer.