2020meai / presrecst

PresRecST

PresRecST: A novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning

1. Introduction

This repository contains source code and datasets for "PresRecST: A novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning".

In this study, we proposed a novel herbal Prescription Recommendation network architecture for real-world patients with integration of Syndrome differentiation and Treatment planning (PresRecST, See Fig1), following the basic diagnostic and treatment process of real-world syndrome differentiation and treatment determination.

2. Overview

Fig1. Framework of PresRecST. The model takes the knowledge embedding matrices of SDTKG and the patient’s symptom set as input, and combines them with the residual-like neural network for recommending syndromes(SDM), treatment methods(TMM) and herbs(HRM) progressively.

3. Data Availability

Due to the sensitive nature of TCM medical data, we have encrypted the currently TCM-Lung dataset. Please contact [email protected] to obtain the decryption password.

4. Citing

If you find PresRecST useful for your research, please consider citing the following paper: Dong X, Zhao C, Song X, Zhang L, Liu Y, Wu J, Xu Y, Xu N, Liu J, Yu H, Yang K, Zhou X. PresRecST: a novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning. J Am Med Inform Assoc. 2024 May 20;31(6):1268-1279.

5. Contact

If you have better suggestions or questions about our work, please contact us: [email protected].

Welcome to follow our project on GitHub: https://github.com/2020MEAI and https://github.com/xdong97 .