Study on Online Doctor Response Adoption Prediction Based on Multimodal Data Mining / 医学信息学杂志
Journal of Medical Informatics
; (12): 44-51, 2024.
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.
Texte intégral:
1
Indice:
WPRIM
langue:
Zh
Texte intégral:
Journal of Medical Informatics
Année:
2024
Type:
Article