Online [Website](http://kmap.xjtudlc.com/pdd) [Github](https://github.com/wangmengsd/pdd-graph) [DataHub](https://datahub.io/tl/dataset/pdd-graph) [SPARQL endpoint](http://kmap.xjtudlc.com/pdd/dataset.html?tab=query&ds=/pdd) You can query some of the data online there. There is also the download link. Of course you can download it here. Context Electronic medical records contain multi-format electronic medical data that consist of an abundance of medical knowledge. Facing with patients symptoms, experienced caregivers make right medical decisions based on their professional knowledge that accurately grasps relationships between symptoms, diagnosis, and treatments. We aim to capture these relationships by constructing a large and high-quality heterogeneous graph linking patients, diseases, and drugs (PDD) in EMRs. Content Specifically, we extract important medical entities from MIMIC-III (Medical Information Mart for Intensive Care III) and automatically link them with the existing biomedical knowledge graphs, including ICD-9 ontology and DrugBank. The PDD graph presented is accessible on the Web via the SPARQL endpoint, and provides a pathway for medical discovery and applications, such as effective treatment recommendations. A subgraph of PDD is illustrated in the followng figure to betterunderstand the PDD graph. ![enter image description here][2] Acknowledgements # Author Data set belongs to Meng Wang, Jiaheng Zhang, Jun Liu,Wei Hu, Sen Wang, , Wenqiang Liu and Lei Shi They come from： 1. MOEKLINNS lab, Xi’an Jiaotong University, Xi’an, China 2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China 3. Griffith Universtiy, Gold Coast Campus, Australia Some Email： - Meng Wang：wangmengsd@stu.xjtu.edu.cn - Lei Shi：xjtushilei@foxmail.com - Jun Liu：liukeen@xjtu.edu.cn # Research The paper is being reviewed and is not easily disclosed.So it can't be linked here. Inspiration If you have any questions, please contact the email address above. Do you have any suggestions ? And send them to an e-mail address above. License [](http://creativecommons.org/licenses/by/4.0/) This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/). If your article needs to be reference our work , you can reference our github. [1]: http://kmap.xjtudlc.com/pdd/ [2]: https://github.com/wangmengsd/pdd-graph/raw/master/example.png