Medical Subject Headings (MeSH), a medical thesaurus created by the National Library of Medicine (NLM), is a useful resource for natural language processing (NLP). In this article, the current status of the Japanese version of Medical Subject Headings (MeSH) is reviewed. Online investigation found that Japanese-English dictionaries, which assign MeSH information to applicable terms, but use them for NLP, were found to be difficult to access, due to license restrictions. Here, we investigate an open-source Japanese-English glossary as an alternative method for assigning MeSH IDs to Japanese terms, to obtain preliminary data for NLP proof-of-concept.
Asian Continental Ancestry Group ; Humans ; Licensure ; Medical Subject Headings ; Methods ; National Library of Medicine (U.S.) ; Natural Language Processing ; Vocabulary, Controlled

The usage of controlled biomedical vocabularies is the cornerstone that enables seamless interoperability when using a common data model across multiple data sites. The Observational Health Data Science and Informatics (OHDSI) initiative combines over 100 controlled vocabularies into its own. However, the OHDSI vocabulary is limited in the sense that it combines multiple terminologies and does not provide a direct way to link them outside of their own self-contained scope. This issue makes the tasks of enriching feature sets by using external resources extremely difficult. In order to address these shortcomings, we have created a linked data version of the OHDSI vocabulary, connecting it with already established linked resources like bioportal, bio2rdf, etc. with the ultimate purpose of enabling the interoperability of resources previously foreign to the OHDSI universe.
Informatics ; Medical Informatics ; Vocabulary ; Vocabulary, Controlled

PURPOSE: The purpose of this study was to analyze the equality between author key words used in the Journal of the Korean Orthopaedic Association and controlled vocabulary or medical subject headings (MeSH). MATERIALS AND METHODS: A total of 1,058 English key words in 320 papers (average 3.3 words in a paper) from 2009 to 2012 were eligible for this study. We classified them according to matched, partially matched, and non-matched terms. The partially matched terms were further dissected into entry terms, qualifiers, anteriorly or posteriorly matched, abbreviations, and pleurals. After descriptive analysis, we assayed patterns of errors in using MeSH, and reviewed frequently used non-MeSH terms. RESULTS: The rate of matched terms was 23.5% for an average of four years, and 34.8% for 2013, which is on the rise by year. The rate of partially matched terms was 34.8%, and that of non-matched terms was 41.7% for an average of four years. The most frequently used key words were Knee and Total knee arthroplasty (17 times), followed by Osteoarthritis (9), Femur, Hip, and Total hip arthroplasty (8). CONCLUSION: Use of proper keywords aligned with the international standards such as MeSH is important to be properly cited. The authors should pay attention and be educated on correct use of MeSH as key words.
Arthroplasty ; Arthroplasty, Replacement, Hip ; Femur ; Hip ; Knee ; Medical Subject Headings* ; Orthopedics ; Osteoarthritis ; Vocabulary, Controlled

OBJECTIVES: Efficient identification of subject experts or expert communities is vital for the growth of any organization. Most of the available expert finding systems are based on self-nomination, which can be biased, and are unable to rank experts. Thus, the objective of this work was to develop a robust and unbiased expert finding system which can quantitatively measure expertise. METHODS: Medical Subject Headings (MeSH) is a controlled vocabulary developed by the National Library of Medicine (NLM) for indexing research publications, articles and books. Using the MeSH terms associated with peer-reviewed articles published from India and indexed in PubMed, we developed a Web-based program which can be used to identify subject experts and subjects associated with an expert. RESULTS: We have extensively tested our system to identify experts from India in various subjects. The system provides a ranked list of experts where known experts rank at the top of the list. The system is general; since it uses information available with the PubMed, it can be implemented for any country. CONCLUSIONS: The expert finding system is able to successfully identify subject experts in India. Our system is unique because it allows the quantification of subject expertise, thus enabling the ranking of experts. Our system is based on peer-reviewed information. Use of MeSH terms as subjects has standardized the subject terminology. The system matches requirements of an ideal expert finding system.
Abstracting and Indexing as Topic ; Bias (Epidemiology) ; Data Mining ; Expert Systems ; India ; Medical Subject Headings* ; National Library of Medicine (U.S.) ; Online Systems ; Professional Competence ; Vocabulary, Controlled

Based on the idea of the ontology, knowledge representation and structure of knowledge base of clinical cases is proposed. The knowledge acquisition process of clinical cases is introduced, the methods of clinical case similarity calculation is proposed; and the experiments of case similarity calculation has been carried on using clinical data calculation is proposed; and the experiments of case similarity calculation has been carried on using clinical data from hospital.
Artificial Intelligence ; Humans ; Knowledge Bases ; Vocabulary, Controlled

Adoption of electronic health records (EHRs) is increasing worldwide. The worldwide EHR adoption rate is estimated to be around 9% to 12%. Thus, the accumulation of medical records in electronic form is also sharply increasing and is expected to be a precious asset for clinical research. Longitudinal observational studies based on EHRs are also increasing. Observational studies covering more than a million people are not rare at present. However, much of the current EHR data are equivalent in form to those of paper records, but are just stored in electronic stor-age devices, rather than as electronic data that can be transferred and shared without loss of clinical semantics. Current EHR systems must be improved in many ways to be used for anal-yses to yield important clinical knowledge. These improvements, which are addressed in this review, include the adoption of clinical data warehouses, use of controlled vocabulary, avoidance of personal/departmental research databases, a standardized interface of many diagnostic devices with the EHR system, control of time-stamp granularity, preparedness for whole-genome sequencing of every patient, confederation or consolidation of multi-institutional EHR data, protection of privacy and confidentiality, and an education system for clinical informaticians.
Adoption ; Confidentiality ; Electronic Health Records ; Electronics ; Electrons ; Humans ; Medical Informatics ; Medical Records ; Privacy ; Semantics ; Vocabulary, Controlled

OBJECTIVES: The purpose of this study is to explore possibility of information sharing between the medical and nursing domains. METHODS: Narrative medical records of 281 hospitalization days of 36 gastrectomy patients were decomposed into single-meaning statements. These single-meaning statements were combined into unique statements by removing semantically redundant statements. Concepts from the statements describing patients' problem and medical procedures were mapped to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and International Classification for Nursing Practice (ICNP) concepts. RESULTS: A total 4,717 single-meaning statements were collected and these single-meaning statements were combined into 858 unique statements. Out of 677 unique statements describing patients' problems and medical procedures, about 85.5% statements were fully mapped to SNOMED CT. The remaining statements were partially mapped. In the mapping to the ICNP concepts, 17.4% of unique statements were fully mapped, 62.8% were partially mapped, and 19.8% were not mapped. About 32.3% of 705 concepts extracted from the statements were mapped to both SNOMED CT and ICNP concepts. CONCLUSIONS: These mapping results suggest that physicians' narrative medical records can be structured and can be used for electronic medical record system, and also it is possible for medicine and nursing to share patient care information.
Electronic Health Records ; Gastrectomy ; Hospitalization ; Humans ; Information Dissemination ; Information Management ; Medical Records ; Patient Care ; Systematized Nomenclature of Medicine ; Vocabulary, Controlled

The International Standard Chinese-English Basic Nomenclature of Chinese medicine (ISN) was released in 2007, a nomenclature list consisting of 6 500 Chinese medical terms. ISN was the culmination of several years of collaborative diligent work of over 200 specialists who represent Chinese medicine in 68 countries. The overall goal for devising standard English nomenclature for Chinese medicine is to develop a practical international standard nomenclature for Chinese medical basic terms, to make it compatible with contemporary research and educational standards in the globalized health care service. In this article, provided is an overview of principles and methods for the multilingual translations, the processes behind the particular content of the Chinese-English ISN and an introduction to the ongoing new projects, i.e. the multilingual versions of ISN (International Standards of Chinese-Spanish, Chinese-French and Chinese-Portuguese Basic Nomenclature of Chinese Medicine).
Anatomy ; standards ; Drugs, Chinese Herbal ; standards ; Humans ; International Cooperation ; Medicine, Chinese Traditional ; methods ; standards ; Multilingualism ; Publications ; standards ; Reference Standards ; Terminology as Topic ; Translating ; Vocabulary, Controlled ; World Health Organization

OBJECTIVETo establish the basis for Chinese dietary exposure assessment database by classifying and coding the data from the national dietary survey and pollutant surveillance.

METHODSThe method, which combined CODEX food classifying and coding of Codex Alimentarius Commission (CAC) with Chinese food classification of food composition table, was applied to classify and code the data of 1 810 703 Chinese dietary consumption and 487 819 pollutant surveillance. The coding system was according to the first two letters of the respective food group that represent the type or source of foods, the last four digits represent the serial number of the food in the CAC food classification. If the foods can be found in CAC food code system, its original food code is used. The new codes corresponding with the foods which are not exist in CAC food code system, is added according to CAC coding methods.

RESULTSDietary consumption data were divided into 6 major categories, 19 types, 75 groups, the agricultural products of pollutant surveillance corresponding to 499 codes. Comparing with CAC food coding system, Chinese dietary consumption data have added F (candy snacks) and G (beverages) 2 major categories, 4 types, 33 groups, 302 new codes. The additional groups most were the processing food groups with Chinese characteristics, such as canned, beverages, candy, meat products.

CONCLUSIONThe foundation of data communication to dietary exposure assessment has been established, and the connection of Chinese food classifying and coding with CAC data have been achieved.

OBJECTIVE: This study compared the abilities of electronic nursing records, which are based on standard nursing terminology, and paper-based nursing records to support the nursing process. METHODS: The nursing records of 38 pairs of inpatients admitted to a gynecology nursing unit were selected. The data from the paper records were obtained manually by a chart review as single statement units. The electronic records were extracted from a computerized system. The statements were categorized using the NANDA diagnosis and the modified Clinical Care Classification. Based on a semantic analysis of the components of the nursing process, the completeness of the nursing records was classified into complete and incomplete patterns according to the presence and relevancy of the assessment, the diagnosis, the intervention and the outcome. RESULTS: The numbers of nursing diagnoses used and the unique nursing diagnoses were both higher in the electronic records than those in the paper records. The number of statements of nursing assessments/outcomes, and nursing interventions was 1.4-fold higher in the electronic records than that in the paper records respectively. The proportion of complete patterns of the nursing process was 3.4% in the paper records and 25.7% in the electronic records. CONCLUSION: These results suggest that electronic records are better than paper records to support the nursing process in terms of the quantitative and qualitative aspects of nursing documentation.
Electronics ; Electrons ; Gynecology ; Humans ; Hysterectomy ; Inpatients ; Medical Records Systems, Computerized ; Nursing Diagnosis ; Nursing Process ; Nursing Records ; Process Assessment (Health Care) ; Semantics ; Vocabulary, Controlled