Abstract: Due to the explosion of online diagnosis and treatment information, the processing and application of diagnosis and treatment information are greatly increased, which greatly hinders the development of online diagnosis and treatment system. Therefore, the research on multi-dimensional feature extraction method of online diagnosis and treatment information based on data mining technology is proposed. The pretreatment online diagnosis and treatment information is filled by cleaning, integration and missing values. The data mining technology-ant colony algorithm is introduced to multi-dimensionally cluster online diagnosis and treatment information. Based on the data mining technology-convolutional neural network, the multi-dimensional feature extraction framework of online diagnosis and treatment information is formulated, and the multi-dimensional features of online diagnosis and treatment information are effectively extracted through the synergy of convolution layer, pooling layer and full connection layer. The experimental results show that there are significant boundaries between the dimensions of patient basic information, patient symptom information, patient treatment process record information and patient follow-up information in the multidimensional clustering results of online diagnosis and treatment information obtained by the proposed method. The characteristics of patient treatment process record information and patient treatment time are consistent with the actual results, which can effectively improve the efficiency and accuracy of diagnosis and treatment information processing and provide practical technical support for the development of online diagnosis and treatment system.

Key words: multi-dimensional feature extraction, online diagnosis and treatment information, multi-dimensional feature fusion, information preprocessing, data mining technology, information clustering