Clinical Text Mining and Efficacy Prediction Studies Using Supervised Topic Models
The clinical texts of patients imply a close relationship between individuals and drug efficacy.In order to solve the problem of the accuracy of anticancer drug efficacy in clinical practice,based on the Supervised Latent Dirichlet Allocation(SLDA),a new method for pharmacodynamic dichotomous prediction B-SLDA was constructed,in which the characteristic representation of patients'clinical texts was obtained,and the mapping relationship with the corresponding pharmacodynamic labels was learned to achieve the prediction purpose.The experimental results show that compared with the traditional feature extraction methods,the proposed method improves the performance of anti-tumor drug efficacy prediction.
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