A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science

2019 ◽  
Vol 119 (3) ◽  
pp. 1455-1486 ◽  
Author(s):  
Zhichao Ba ◽  
Yujie Cao ◽  
Jin Mao ◽  
Gang Li
1989 ◽  
Vol 28 (04) ◽  
pp. 273-280 ◽  
Author(s):  
J. Möhr

Abstract:This paper reviews different concepts of medical informatics and identifies two families of approaches to education in it: a “specialist” approach, whereby medical informatics is taught as a specialization track for established disciplines like medicine, computer science, nursing, engineering, etc., and a “generalistic” approach, whereby it is taught as an integrated discipline incorporating essential traits of the aforementioned disciplines. The pros and cons of these approaches are outlined. The need to accommodate specific requirements of education is emphasized and these are identified, together with an outline of particular challenges that we are facing.


Author(s):  
Abeer A. Amer ◽  
Soha M. Ismail

The following article has been withdrawn on the request of the author of the journal Recent Advances in Computer Science and Communications (Recent Patents on Computer Science): Title: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC) Authors: Abeer A. Amer and Soha M. Ismail* Bentham Science apologizes to the readers of the journal for any inconvenience this may cause BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.


2014 ◽  
Vol 7 (3) ◽  
pp. 291-301 ◽  
Author(s):  
Maria-Blanca Ibanez ◽  
Angela Di-Serio ◽  
Carlos Delgado-Kloos

2021 ◽  
Vol 20 (01) ◽  
pp. 2150011
Author(s):  
Worapan Kusakunniran ◽  
Thearith Ponn ◽  
Nuttapol Boonsom ◽  
Suwimol Wahakit ◽  
Kittikhun Thongkanchorn

This paper develops the Scopus H5-Index rankings, using the field of computer science as a case study. The challenge begins with the inconsistency of conference names. The rule-based approach is invented to automatically clean up duplicate conferences and assign unique pseudo ID for each conference. This data cleansing process is applied on conference names retrieved from both Scopus and ERA/CORE, in order to share common pseudo IDs for the sake of correlation analysis. The proposed data cleansing process is validated using ERA 2010 and CORE 2018 as references and reports the very small errors of 0.6% and 0.4%, respectively. Then, the Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018 rankings are constructed and compared with the existing ERA 2010 and CORE 2018 rankings, respectively. The results show that the correlation within the Scopus H5-Index rankings (i.e. Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018) is at the top of the moderate correlation band, where the correlation within the ERA/CORE rankings (ERA 2010 and CORE 2018) is at the top of the strong correlation band. While the correlations across ranking systems (i.e. Scopus H5-Index 2006–2010 vs. ERA 2010, and Scopus H5-Index 2014–2018 vs. CORE 2018) are at the bottom and middle of the moderate correlation band. It can be said that the quality assessment using the Scopus H5-Index ranking is more dynamic and quickly up-to-date when compared with the ERA/CORE ranking. Also, these two ranking systems are moderately correlated with each other for both periods of 2010 and 2018.


2021 ◽  
Vol 9 (1) ◽  
pp. 238-245
Author(s):  
Feiheng Luo ◽  
Aixin Sun ◽  
Aravind Sesagiri Raamkumar ◽  
Mojisola Erdt ◽  
Yin-Leng Theng

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