Parsed the ECG descriptions in DICOM 3.0 standard and accomplished a DICOM-ECG file which conforms to the DICOM standard by a toolkit DCMTK. The DICOM-ECG file can communicate with systems which support DICOM standard directly.
Electrocardiography ; instrumentation ; methods ; Information Storage and Retrieval ; Software

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.
Dataset ; Information Storage and Retrieval ; Methods ; Semantics ; Vocabulary

It is our great pleasure to announce that the Taehan Kan Hakhoe Chi (The Korean Journal of Hepatology) was approved for listing, from 2002, in the Index Medicus, Medline/PubMed of the National Library of Medicine, NIH of USA. Herein, I review the searching tools employing a Medical Subject Heading (MeSH) such as liver disease and liver neoplasm or an author index for this Journal in the PubMed at a website. Of course, The Korean Journal of Hepatology should be continually striving to be upgraded. Dream comes true.
*Gastroenterology ; Information Storage and Retrieval/*methods ; Korea ; *MEDLARS ; *MEDLINE ; *PubMed

To extract texture features from medical images, the approaches for multi-scale complexity and multi-scale fractal dimension were proposed in this paper. The extracted texture features were used in the medical image retrieval experiments. The complexity measurements used include permutation entropy and 2D-C0 complexity. The former is used to analyze one dimensional signal, and the latter is used to analyze two dimensional one. Comparison experiments were carried out between our approaches and others' approaches in some literatures. Preliminary experimental results show that our approaches can effectively describe the texture information of medical images. Furthermore, the image retrieval results are encouraging.
Automation ; Diagnostic Imaging ; Humans ; Information Storage and Retrieval ; methods ; Nonlinear Dynamics

This paper introduces the design and development of a teleimaging diagnosis system by using B/S mode. A detailed design on the telediagnosis process and telediagnosis management is presented, focusing on resolving medical image transmission, management and display in the internet, and is trying to integrate the teleimaging diagnosis system with PACS.
Diagnostic Imaging ; Information Storage and Retrieval ; Internet ; Software Design ; Teleradiology ; methods

As traditional data management model cannot effectively manage the massive data in traditional Chinese medicine(TCM) due to the uncertainty of data object attributes as well as the diversity and abstraction of data representation, a management strategy for TCM data based on big data technology is proposed. Based on true characteristics of TCM data, this strategy could solve the problems of the uncertainty of data object attributes in TCM information and the non-uniformity of the data representation by using modeless properties of stored objects in big data technology. Hybrid indexing mode was also used to solve the conflicts brought by different storage modes in indexing process, with powerful capabilities in query processing of massive data through efficient parallel MapReduce process. The theoretical analysis provided the management framework and its key technology, while its performance was tested on Hadoop by using several common traditional Chinese medicines and prescriptions from practical TCM data source. Result showed that this strategy can effectively solve the storage problem of TCM information, with good performance in query efficiency, completeness and robustness.
Big Data ; Information Storage and Retrieval ; methods ; Medicine, Chinese Traditional

This article elaborates key points of the PACS and RIS project: its overall planning, implementation step by step, integration of PACS and HIS based on IHE, and the prudent selection of partners and so on.
Hospital Information Systems ; Humans ; Information Storage and Retrieval ; methods ; Radiology Information Systems ; Software ; Systems Integration

In this paper, we have brought forward the framework design of DICOM software platform, using the SUR-DICOM-Lib software and have completed the connection test with the RSNA-CTNT Test Node. PACS, DICOM, realize
Computer Communication Networks ; Equipment Design ; Humans ; Information Storage and Retrieval ; methods ; Radiology Information Systems ; Software ; Software Design

This paper introduces the basic principle and method of establishing a database for neuropathic images, and discusses its significance and data sharing. The database is composed of three data volumes about basic knowledge for images, cranial sectional anatomy and neuropathic images. The data sharing is achieved by using a method of linking the dynamic network of neuropathic images with database of neuropathic images. There are three searching approaches: catalog searching, key words searching and code searching.
Databases, Bibliographic ; Hospital Information Systems ; Humans ; Information Storage and Retrieval ; methods ; Neuroradiography

Clinic expert information provides important references for residents in need of hospital care. Usually, such information is hidden in the deep web and cannot be directly indexed by search engines. To extract clinic expert information from the deep web, the first challenge is to make a judgment on forms. This paper proposes a novel method based on a domain model, which is a tree structure constructed by the attributes of search interfaces. With this model, search interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from the returned web pages indexed by search interfaces. To filter the noise information on a web page, a block importance model is proposed. The experiment results indicated that the domain model yielded a precision 10.83% higher than that of the rule-based method, whereas the block importance model yielded an F₁ measure 10.5% higher than that of the XPath method.
Hospital Information Systems ; Information Storage and Retrieval ; methods ; Internet ; User-Computer Interface