Machine-learning Based Prediction Model in Primary Immune Thrombocytopenia

This observational and prospective study developed through Peking University aims to test a novel machine learning algorithm to identify which individuals with ITP are at an increased risk for a critical bleed. The tool used to generate the algorithm is a web-based resource to integrate clinical and laboratory data across multiple centers in China to build a clinical prediction model. The study target is ITP patients who are newly diagnosed; however, eligibility includes all adults over the age of 18 years with a confirmed diagnosed of ITP.



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