Premature infant PICC (Peripherally Inserted Central Catheter) secondary displacement risk prediction method and system

The invention provides a premature infant PICC catheter secondary displacement risk prediction method and system, a storage medium and electronic equipment, and relates to the technical field of medical instruments. According to the method, three machine learning methods of a random forest classifier, an Adaboost algorithm and an SVM classifier are adopted, a first secondary shift risk prediction model, a second secondary shift risk prediction model and a third secondary shift risk prediction model are constructed respectively, the first secondary shift risk prediction model, the second secondary shift risk prediction model and the third secondary shift risk prediction model are fused based on the risk prediction accuracy of each model, and a final risk prediction model is obtained. Obtaining a prediction result of the secondary displacement risk of the to-be-detected early-growing child after the to-be-detected early-growing child is placed into the PICC catheter; the method can accurately and efficiently id