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What is JCP 78 10 about?

This research investigates the use of machine learning algorithms to predict polycythaemia vera (PV) disease based on complete blood count parameters, aiming to reduce reliance on costly diagnostic tests. The study involved 1484 patients, with the XGBoost algorithm demonstrating the highest accuracy in predicting PV. The findings suggest that ML can effectively diagnose PV, potentially streamlining the diagnostic process and minimizing patient stress and healthcare costs.

Author

marrowbiopsy

Language

EN