Study on Online Doctor Response Adoption Prediction Based on Multimodal Data Mining

VernacularTitle:基于多模态数据挖掘的网络医生答复采纳预测研究
Author: Weiwei DENG ¹ ; Tianwei YU ; Han CHEN ; Guohe FENG
Author Information

1. 华南师范大学经济与管理学院广州 510006
Keywords: online healthcare; response adoption prediction; multimodal data mining; machine learning
From: Journal of Medical Informatics 2024;45(2):44-51
CountryChina
Language:Chinese
Abstract: 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.