Your browser doesn't support javascript.
loading
Study on Online Doctor Response Adoption Prediction Based on Multimodal Data Mining / 医学信息学杂志
Article de Zh | WPRIM | ID: wpr-1023490
Bibliothèque responsable: WPRO
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.
Mots clés
Texte intégral: 1 Indice: WPRIM langue: Zh Texte intégral: Journal of Medical Informatics Année: 2024 Type: Article
Texte intégral: 1 Indice: WPRIM langue: Zh Texte intégral: Journal of Medical Informatics Année: 2024 Type: Article