Abstract: The present invention includes techniques for data processing and particularly relates to a method and system for predicting human fall risk based on electronic nursing text (ENT) data. The method comprises the following steps: obtaining an ENT data set, pre-processing data in the ENT data set, and constructing a Morse Fall Scale (MFS) dictionary with the pre-processed data; extracting features from the ENT data of patients to be predicted with a natural language processing technology; analyzing the extracted text features by the MFS dictionary to obtain a data set of risk factors; training a decision tree algorithm by using the data set of risk factors to obtain a prediction result of the patient's fall risk; clustering and precisely nursing the patients according to the prediction result.

Abstract: An electrode core includes a negative electrode, a negative electrode tab, and a positive electrode sheet. The negative electrode sheet includes a negative electrode current collector and a negative electrode active material attached to the negative electrode current collector, and a negative electrode tab groove is disposed on the negative electrode active material. The negative electrode tab is disposed in the negative electrode tab groove. The positive electrode sheet includes a positive electrode current collector and a positive electrode active material attached to the positive electrode current collector. A first groove is disposed on the positive electrode active material, the first groove disposed is opposite to the negative electrode tab groove, and a projection of the first groove on the negative electrode sheet is located in the negative electrode tab groove.