However, the current medical information systems have aimed for digitalizaing, storing, and transferring clinical materials.
Clinical materials from patients before, during and after treatments withclinical end points are being collected.
After then, many studies [1 7] have aimed for efficient storing, sharing, and transferring electronic clinical materials, and some works [8, 9] have proposed methods to analyze and process individual clinical materials like medical images or videos.
Non-peer reviewed clinical materials were collated from a range of sources.
Therefore, a new method is necessary to semantically converge and manage medical data instead of clinical materials like documents and images/videos.
Medical data includes common parts such as a patient's basic profile and vital information, but clinical materials (documents, examination results, etc).
In order to reflect the disease-specificity in a data model, we collected and analyzed eight clinical materials which are essential for the diagnoses and treatments of AMI.
Recently, rather than electronically storing clinical materials or processing each data, the needs for discovering meanings from medical big data and utilizing them have significantly increased.
However, since they just focused on one type of clinical materials, they did not consider heterogeneous data in EMR or PACS.
As mentioned in the introduction section, the modeling of data contained in clinical materials is necessary for intelligent utilization of medical information.
The authors would like to thank the following individuals who have contributed to ascertainment of clinical materials and data.
