Study on Online Doctor Response Adoption Prediction Based on Multimodal Data Mining
Purpose/Significance To use multimodal data analysis method to mine medical Q&A data in online healthcare platforms and predict whether patients will adopt online doctors'responses.Method/Process First,numerical,categorical,textual,and visual data related to doctor-patient Q&A are obtained from online healthcare platforms,and three datasets of acute disease,chronic disease and mixed disease are constructed according to disease types.Then,normalization,one-hot encoding,Med-BERT,and convolutional neural network are used respectively to process numerical,categorical,textual,and visual data.Finally,a gradient boosting decision tree is used to predict whether patients will adopt online doctors'responses.Result/Conclusion Doctors'profile pictures can improve the prediction effect of online doctor response adoption,and multimodal data mining can effectively predict the response adoption.
online healthcareresponse adoption predictionmultimodal data miningmachine learning
万方数据
维普
