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DC Proposal: Decision Support Methods in Community-Driven Knowledge Curation Platforms
[chapter]
2011
Lecture Notes in Computer Science
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We aim to develop decision support methods in the skeletal dysplasia domain by applying uncertainty reasoning over Semantic Web data. ...
in the field. ...
The work presented in this paper is supported by the Australian Research Council (ARC) under the Linkage grant SKELETOME -LP100100156. ...
doi:10.1007/978-3-642-25093-4_26
fatcat:odrqyckyevb2ljysbw2awv76nu
Brain Tumor Diagnosis Support System: A Decision Fusion Framework
2020
IRA-International Journal of Applied Sciences (ISSN 2455-4499)
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The fusion process is based on the Dempster Shafer evidence fusion theory. Several tumor classifiers are employed. ...
Current image-based tumor detection and diagnosis methods depend heavily on the interpretation of the neuro specialists and/or radiologists. ...
as ANN, support vector machine shown by SVM, and the Dempster-Shafer Theory. ...
doi:10.21013/jas.v15.n3.p1
fatcat:dgpjuaezjrabzmxqvcg3z3mzsa
Decision Support Methods for Finding Phenotype — Disorder Associations in the Bone Dysplasia Domain
2012
PLoS ONE
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We propose a solution that combines association rule mining with the Dempster-Shafer theory (DST) to compute probabilistic associations between sets of clinical features and disorders, which can then serve ...
as support for medical decision making (e.g., diagnosis). ...
Acknowledgments We gratefully acknowledge the anonymous reviewers whose comments and advices have helped us improve our manuscript. ...
doi:10.1371/journal.pone.0050614
pmid:23226331
pmcid:PMC3511538
fatcat:7ci5ixiehrh5lc4qy6eg6jw2ty
Integration of Artificial Intelligence into Dempster Shafer Theory: A Review on Decision Making in Condition Monitoring
2015
Applied Mechanics and Materials
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This paper reviews the techniques used for automated decision making in CM with emphasis given on Dempster-Shafer (D-S) evident theory and other basic probability assignment (BPA) techniques such as support ...
The advent of artificial intelligence (AI) and automated ways for decision making in CM provides a more objective and unbiased approach for CM industry and has become a topic of interest in the recent ...
D-S Theory On 1976, Shafer established the Dempster theory which is proposed as an alternative to Bayesian inference theory. ...
doi:10.4028/www.scientific.net/amm.773-774.154
fatcat:cgk7movrefaw7cbphojfcinx7m
Evidence combination in medical data mining
2004
International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.
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In this work we apply Dempster-Shafer's theory of evidence combination for mining medical data. We consider the classification task in two domains: breast tumors and skin lesions. ...
We combine the beliefs of three classifiers: k-Nearest Neighbor (kNN), Naïve Bayesian and Decision Tree. Dempster's rule of combination combines three beliefs to arrive at one final decision. ...
Association rules can be extracted from this tree. An association rule has support and confidence associated with it.where numerator indicates the number of records with A and B both true. ...
doi:10.1109/itcc.2004.1286697
dblp:conf/itcc/AslandoganMT04
fatcat:7vlep4jdczcljnbmxy2q2e5qe4
Fusion of FNA-cytology and Gene-expression Data Using Dempster-Shafer Theory of Evidence to Predict Breast Cancer Tumors
2006
Bioinformation
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In this paper, Dempster-Shafer Theory (DST) has been used to fuse classification results of breast cancer data from two different sources: gene-expression patterns in peripheral blood cells and Fine-Needle ...
Decision-in decision-out fusion architecture can be used to fuse the outputs of multiple classifiers from different diagnostic sources. ...
"Malignant", Dempster-Shafer theory gives a rule of combining data source Di's outcome mi and data source Dj's outcome mj ∑ ∑ = ∩ ′ = ∩ ′ ′ ′ − = ⊕ φ k k k k E E k j k i M E E k j k i j i E m E m E m E ...
doi:10.6026/97320630001170
pmid:17597882
pmcid:PMC1891684
fatcat:uvowkdakmjbnvm5lsys3lu524a
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020)
[article]
2020
arXiv
pre-print
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This paper reviewed related studies conducted in the last 30 years (from 1991 to 2020) in handling uncertainties in medical data using probability theory and machine learning techniques. ...
The sources of noise in the medical data need to be known to address this issue. Based on the medical data obtained by the physician, diagnosis of disease, and treatment plan are prescribed. ...
Data availability The authors declare that all data supporting the findings of this study are available within the paper and its Supplementary Information. ...
arXiv:2008.10114v1
fatcat:pgiep5djj5bdpe7qr4n2f4buky
A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing
2020
Shock and Vibration
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To solve the above problems, a multimodel decision fusion method based on Deep Convolutional Neural Network and Improved Dempster-Shafer Evidence Theory (DCNN-IDST) is proposed for the inspection of rolling ...
To solve the defect of the original evidence theory method in the fusion of high-conflict evidence, the fuzzy consistency matrix is introduced. ...
B n . e combination rule of Dempster-Shafer evidence theory is defined as follows: m(A) � Ai ∩ Bj�A m 1 (Ai)m 2 (Bj) 1 − Ai ∩ Bj�ϕ m 1 (Ai)m 2 (Bj). (5) (3) e new improved method of Dempster-Shafer ...
doi:10.1155/2020/8856818
fatcat:5ie2qvccyvbdziq7rwbcg6cbhi
Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020)
2021
Annals of Operations Research
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This paper reviewed related studies conducted in the last 30 years (from 1991 to 2020) in handling uncertainties in medical data using probability theory and machine learning techniques. ...
Machine learning and probability theory methods have been widely used for this purpose in various fields. ...
Authors in (Porebski et al., 2018) proposed a diagnosis support method and a rule selection both by applying fuzzy set and Dempster-Shafer theories. ...
doi:10.1007/s10479-021-04006-2
pmid:33776178
pmcid:PMC7982279
fatcat:wq2eweu7hfduvbhwo5oaqaltoe
An Improved Multisensor Data Fusion Method and Its Application in Fault Diagnosis
2019
IEEE Access
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INDEX TERMS Conflict evidence, Dempster's combination rule, belief entropy, Dempster-Shafer evidence theory, information theory. 3928 2169-3536 ...
Moreover, the fusion results using different methods are analyzed, which indicate the superiority and stronger application of the proposed method in the field of fault diagnosis. ...
Dempster-Shafer evidence theory (D-S theory), also referred to as the theory of belief functions, is proposed by Dempster [18] and developed later by Shafer et al. [19] . ...
doi:10.1109/access.2018.2889358
fatcat:cpjpqvm67jcaho7i7jzftvvytm
Toward Normative Expert Systems: Part I The Pathfinder Project
1992
Methods of Information in Medicine
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The program is one of a growing number of normative expert systems that use probability and decision theory to acquire, represent, manipulate, and explain uncertain medical knowledge. ...
Then, we describe experimental and theoretical results that directed us to return to reasoning methods based in probability and decision theory. ...
Computational support has been provided in part by the SUMEX-AIM resource under National Institutes of Health Grant LM05208. ...
doi:10.1055/s-0038-1634867
fatcat:5dhpf2dnofgffhvnsbzmhtb2we
Predicting Stroke Risk with an Interpretable Classifier
2020
IEEE Access
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The rules were validated by both medical literature and human specialists. INDEX TERMS Dempster-Shafer theory, stroke, expert systems, interpretable classification. ...
It is based on the Dempster-Shafer theory of plausibility. ...
DEMPSTER-SHAFER THEORY The Dempster-Shafer Theory (DST) [22] is a mathematical framework to reason with uncertainty and incomplete data. ...
doi:10.1109/access.2020.3047195
fatcat:tjyfo2byz5gjbahyafbqejgpdu
Page 7911 of Mathematical Reviews Vol. , Issue 99k
[page]
1999
Mathematical Reviews
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7911
transformations among the Dempster-Shafer theory, possibility theory and probability theory. ...
These transformations are based on a well-justified measure of uncertainty in the Dempster-Shafer theory. ...
Bayesian and Dempster–Shafer reasoning for knowledge-based fault diagnosis–A comparative study
2017
Engineering applications of artificial intelligence
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are handled in two well-known frameworks, namely the Bayesian and the Dempster-Shafer reasoning framework. ...
In contrast to previous works, which take the reasoning method as the starting point, we start from the application, knowledge-based fault diagnosis, and examine the effectiveness of different reasoning ...
Reasoning in D-S networks We adopt Smets' Transferable Belief Model (TBM) interpretation of the Dempster-Shafer theory [30] . ...
doi:10.1016/j.engappai.2017.01.011
fatcat:xx2xgzqx3rbtbjuy3c5qputea4
A modified approach to conflict management from the perspective of non-conflicting element set
2020
IEEE Access
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In Dempster-Shafer (D-S) evidence theory, how to deal with conflict is an important and open topic. ...
INDEX TERMS Dempster-Shafer (D-S) evidence theory, correlation coefficient, non-conflicting element set, conflict management. ...
ACKNOWLEDGMENT The authors thank the anonymous reviewers for their valuable suggestions and comments. ...
doi:10.1109/access.2020.2988036
fatcat:m5jij4fm3zczloaojytd3wsppa
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