지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.13 No.4
- 발행연도
- 2019.12
- 수록면
- 151 - 162 (12page)
- DOI
- 10.5626/JCSE.2019.13.4.151
이용수
초록· 키워드
오류제보하기
In medical decision-making, pros and cons of balancing treatment options are often required. However, clinical experts may well put forward their opinions on the basis of huge uncertain or incomplete information. To address this issue, the notion of hesitant neutrosophic concept lattice (HNCL) has been utilized to express the decision information based on hesitant neutrosophic sets (HNS) and formal concept analysis (FCA). Here, we present another improved hybrid model to measure the similarity distance among hesitant neutrosophic concepts (HNCon). An actual example was used to demonstrate the effectiveness and reliability of the proposed method.
목차
Abstract
I. Introduction
II. CONCEPT LATTICE WITH HESITANT NEUTROSOPHIC SETTING
III. PROPOSED METHOD
IV. MEDICAL DECISION-MAKING BASED ON HNCL
V. CONCLUSIONS
REFERENCES
참고문헌 (43)
참고문헌 신청
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Y. X. Song, C. C. Zhang, and Y. S. Shi, “Extracting algorithm for diagnostic parameters of aero-engine based on fuzzy-rough sets,” Journal of Aerospace Power, vol. 23, no. 6, pp. 1127-1130, 2008.
S. Vajda, D. You, S. K. Antani, and G. R. Thoma, “Label the many with a few: semi-automatic medical image modality discovery in a large image collection,” in Proceedings of 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), Orlando, FL, 2014, pp. 167-173.
E. Zaitseva, M. Kvassay, V. Levashenko, and J. Kostolny, “Introduction to knowledge discovery in medical databases and use of reliability analysis in data mining,” in Proceedings of 2015 Federated Conference on Computer Science and Information Systems (FedCSIS), Lodz, Poland, 2015, pp. 311-320.
A. Holzinger, R. Scherer, M. Seeber, J. Wagner, and G. Muller-Putz, “Computational sensemaking on examples of knowledge discovery from neuroscience data: towards enhancing stroke rehabilitation,” in Information Technology in Bio- and Medical Informatics. Heidelberg: Springer, 2012, pp. 166-168.
Y. X. Song, C. C. Zhang, and Y. S. Shi, “Extracting algorithm for diagnostic parameters of aero-engine based on fuzzy-rough sets,” Journal of Aerospace Power, vol. 23, no. 6, pp. 1127-1130, 2008.
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