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In order to promote the application of machine learning in intelligent manufacturing, especially in medical products and intelligent hospitals, based on the theoretical research of machine learning under big data, intelligent medical disease diagnosis and classification products are designed. Two algorithms, MLP and SVM, are used to compare the accuracy, recall and F1. It is concluded that the effect of medical diagnosis classification of both methods is maintained above and below 90%. At the same time, the research proves that the corresponding accuracy can be improved only when the fuzzy matching is suitable for more positive examples.

enterprise information systems

Analysis and research on intelligent manufacturing medical product design and intelligent hospital system dynamics based on machine learning under big data