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A Topic Modeling Approach for Traditional Chinese Medicine Prescriptions. TKDE 2018

Project README

PTM

The dataset and implementation of Prescription Topic Model in our paper:

Liang Yao, Yin Zhang, Baogang Wei, Wenjin Zhang, Zhe Jin. (2018). "A Topic Modeling Approach for Traditional Chinese Medicine Prescriptions". IEEE Transactions on Knowledge and Data Engineering (TKDE) 30(6), pp.1007-1021.

Require

Java 7 or above, I use Java 8 in this project.

Eclipse

Data

The Copyright holder of the dataset is China Knowledge Centre for Engineering Sciences and Technology (CKCEST). The dataset is for research use only. Any commercial use, sale, or other monetization is prohibited.

98,334 raw prescriptions with herbs and symptoms are in /data/prescriptions.txt . Each line is for a prescription, symptoms are on the left and herbs are on the right.

The preprocessed 33,765 prescriptions: /data/pre_herbs.txt, /data/pre_symptoms.txt.

Training set: /data/pre_herbs_train.txt, /data/pre_symptoms_train.txt

Test set: /data/pre_herbs_test.txt, /data/pre_symptoms_test.txt

Note:

  1. Each line in above files is for a prescription, the same line in /data/pre_herbsX.txt and /data/pre_symptomsX.txt (X is _train or _test or ' ' ) is for the same prescription.

  2. Each number in above files means an herb or a symptom, each number is an index of the following herb list or symptom list. For example, '5' in /file/pre_herbs_train.txt means the 6th herb in the herb list /data/herbs_contains.txt, '17' in /file/pre_symptoms_train.txt means the 18th symptom in the symptom list /data/symptom_contains.txt.

Herb list: /data/herbs_contains.txt

Symptom list: /data/symptom_contains.txt

TCM MeSH herb-symptom correspondence knowledge: /data/symptom_herb_tcm_mesh.txt

Symptom Category: /data/symptom_category.txt

Demo

PTM(a): /src/test/RunPTMa.java (reproducing prescribing patterns discovery results)

PTM(b): /src/test/RunPTMb.java

PTM(c): /src/test/RunPTMc.java

PTM(d): /src/test/RunPTMd.java

Herbs and symptoms prediction/recommendation tasks

(reproducing herbs/symptoms predictive perplexity and precision@N results)

PTM(a): /src/test/PTMaPredict.java

PTM(b): /src/test/PTMbPredict.java

PTM(c): /src/test/PTMcPredict.java

PTM(d): /src/test/PTMdPredict.java

Topic herb precision

/src/test/TopicPrecisionSymToHerb.java

Prescription predictive perplexity

PTM(a): src/perplexity/PTMaPerplexity.java

PTM(b): src/perplexity/PTMbPerplexity.java

PTM(c): src/perplexity/PTMcPerplexity.java

PTM(d): src/perplexity/PTMdPerplexity.java

Topic symptom coherence

/src/test/TopicKnowCoherence.java

Open Source Agenda is not affiliated with "PTM" Project. README Source: yao8839836/PTM
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