Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Radiological Physics and Technology
Published in: Radiological Physics and Technology 2/2010

01-07-2010

Quantitative analysis of ontology research articles in the radiologic domain

Authors: Naoki Nishimoto, Ayako Yagahara, Yuki Yokooka, Shintaro Tsuji, Masahito Uesugi, Katsuhiko Ogasawara, Masaji Maezawa

Published in: Radiological Physics and Technology | Issue 2/2010

Login to get access

Abstract

To investigate the most advanced ontology research in health care and its impact on the radiologic domain, we proposed a concept identification and abstraction technique called “Concept Step”. This technique identifies a MeSH term, medical subject headings used in PubMed, in a sentence and climbs up through its hierarchy to reach an abstract concept. We developed original Java software to implement this technique. We tested it on 2,774 abstracts in health-care ontology research retrieved from MEDLINE on 23 October 2008. The total number of MeSH terms was 112,690. We counted a total of 33 MeSH terms (0.029%) in the radiologic domain. The most frequently occurring term was “radiology”, which occurred 21 times in the article set. Other frequent terms were “magnetic resonance imaging” and “tomography”, the counts of which were 4 and 3, respectively. A pair plot showed no correlation among the MeSH categories “Analytical Diagnostic and Therapeutic Techniques and Equipment”, “Anatomy”, “Biological Sciences”, and “Chemicals and Drugs”. We conclude that ontology research is well established in the biomedical domain, and that further study is required in the radiologic domain.
Literature
1.
Zhao L, Lee KP, Hu J. Generating XML schemas for DICOM structured reporting templates. J Am Med Inform Assoc. 2005;12(1):72–83.CrossRefPubMed
2.
Lee KP, Hu J. XML schema representation of DICOM structured reporting. J Am Med Inform Assoc. 2003;10(2):213–23.CrossRefPubMed
3.
Rubin DL, Noy NF, Musen MA. Protege: a tool for managing and using terminology in radiology applications. J Digit Imaging. 2007;20(Suppl 1):34–46.CrossRefPubMed
4.
Gruber T. A translation approach to portable ontology specifications. Knowledge Systems Laboratory Technical Report KSL 92-71. 1993:1–26.
5.
Genesereth MR, Nilsson NJ. Logical foundations of artificial intelligence. San Mateo, CA: Morgan Kaufmann Publishers; 1987.
6.
7.
Langlotz CP. RadLex: a new method for indexing online educational materials. Radiographics. 2006;26(6):1595–7.
8.
Kundu S, Itkin M, Gervais DA, Krishnamurthy VN, Wallace MJ, Cardella JF, et al. The IR Radlex Project: An Interventional Radiology Lexicon-A Collaborative Project of the Radiological Society of North America and the Society of Interventional Radiology. J Vasc Interv Radiol. 2008;20:433–5.CrossRefPubMed
9.
Marwede D, Schulz T, Kahn T. Indexing thoracic CT reports using a preliminary version of a standardized radiological lexicon (RadLex). J Digit Imaging. 2008;21(4):363–70.CrossRefPubMed
10.
Marwede D, Daumke P, Marko K, Lobsien D, Schulz S, Kahn T. RadLex—German version: a radiological lexicon for indexing image and report information. Rofo. 2009;181(1):38–44.PubMed
11.
Al-Mubaid H, Nguyen HA. A cluster-based approach for semantic similarity in the biomedical domain. Conf Proc IEEE Eng Med Biol Soc. 2006;1:2713–7.CrossRefPubMed
12.
Andreopoulos B, Alexopoulou D, Schroeder M. Word sense disambiguation in biomedical ontologies with term co-occurrence analysis and document clustering. Int J Data Mining Bioinform. 2008;2(3):193–215.CrossRef
13.
Bodenreider O, Mitchell JA, McCray AT. Biomedical ontologies. Pac Symp Biocomput. 2005:76–8.
14.
Pakhomov SV, Hanson PL, Bjornsen SS, Smith SA. Automatic classification of foot examination findings using clinical notes and machine learning. J Am Med Inform Assoc. 2008;15(2):198–202.CrossRefPubMed
15.
Pakhomov SV, Coden A, Chute CG. Developing a corpus of clinical notes manually annotated for part-of-speech. Int J Med Inf. 2006;75(6):418–29.CrossRef
16.
Pakhomov SV, Buntrock JD, Chute CG. Using compound codes for automatic classification of clinical diagnoses. Stud Health Technol Inform. 2004;107(Pt 1):411–5.PubMed
17.
Pakhomov SV, Ruggieri A, Chute CG. Maximum entropy modeling for mining patient medication status from free text. Proc Amia Symp. 2002:587–91.
18.
Savova GK, Coden AR, Sominsky IL, Johnson R, Ogren PV, de Groen PC, et al. Word sense disambiguation across two domains: biomedical literature and clinical notes. J Biomed Inform. 2008;41(6):1088–100.CrossRefPubMed
19.
Witten IH, Frank E. Data mining: practical machine learning tools and techniques with Java implementations. SIGMOD Rec. 2002;31(1):76–7.CrossRef
20.
Yamamoto Y, Takagi T. Biomedical knowledge navigation by literature clustering. J Biomed Inform. 2007;40(2):114–30.CrossRefPubMed
21.
Xu H, Stetson PD, Friedman C. Methods for building sense inventories of abbreviations in clinical notes. J Am Med Inform Assoc. 2009;16(1):103–8.CrossRefPubMed
22.
Witten I, Frank E. Data mining: practical machine learning tools and techniques with Java implementations. San Francisco: Morgan Kaufmann; 1999.
23.
Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 2004;32(Database issue):D267–70.
Metadata
Title
Quantitative analysis of ontology research articles in the radiologic domain
Authors
Naoki Nishimoto
Ayako Yagahara
Yuki Yokooka
Shintaro Tsuji
Masahito Uesugi
Katsuhiko Ogasawara
Masaji Maezawa
Publication date
01-07-2010
Publisher
Springer Japan
Published in
Radiological Physics and Technology / Issue 2/2010
Print ISSN: 1865-0333
Electronic ISSN: 1865-0341
DOI
https://doi.org/10.1007/s12194-010-0094-x

Other articles of this Issue 2/2010

Radiological Physics and Technology 2/2010 Go to the issue

OriginalPaper

Perturbation correction factors for cylindrical ionization chambers in high-energy electron beams

OriginalPaper

Optimization of dual electron multileaf collimator materials by use of EGSnrc

OriginalPaper

A study on the validity of quantitative ultrasonic measurement used the bone mineral density values on dual-energy X-ray absorptiometry in young and in middle-aged or older women

OriginalPaper

Nationwide survey on the operational status of electron accelerators for radiation therapy in Japan

OriginalPaper

Microdosimetric investigation of the spectra from YAYOI by use of the Monte Carlo code PHITS

OriginalPaper

Comparison of detectability of a simple object with low contrast displayed on a high-brightness color LCD and a monochrome LCD