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Efficient discovery of risk patterns in medical data

Jiuyong Li, Ada Wai-chee Fu, Paul Fahey
2009 Artificial Intelligence in Medicine  
Result: The proposed approach is compared with two well known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application  ...  We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm.  ...  Acknowledgements This research has been supported by ARC DP0559090, the RGC Earmarked Research Grant of HKSAR CUHK 4179/01E, and the Innovation and Technology Fund (ITF) in the HKSAR [ITS/069/03].  ... 
doi:10.1016/j.artmed.2008.07.008 pmid:18783927 fatcat:nrfzlexmpnaupbtthcqszhdy3u

IMDS

Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye
2007 Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '07  
IMDS is an integrated system consisting of three major modules: PE parser, OOA rule generator, and rule based classifier.  ...  data mining based detection systems which employed Naive Bayes, Support Vector Machine (SVM) and Decision Tree techniques.  ...  Acknowledgments The work of Tao Li is partially supported by NSF IIS-0546280.  ... 
doi:10.1145/1281192.1281308 dblp:conf/kdd/YeWLY07 fatcat:4bi5fgvq6nd5ddkrtra5ams7gq

Multicriteria Attractiveness Evaluation of Decision and Association Rules [chapter]

Izabela Szczȩch
2009 Lecture Notes in Computer Science  
It analyses desirable properties (in particular the property M, property of confirmation and hypothesis symmetry) of popular interestingness measures of decision and association rules.  ...  It's main result is a proposition of a multicriteria evaluation space in which the set of non-dominated rules will contain all optimal rules with respect to any attractiveness measure with the property  ...  The author gratefully acknowlegdes anonymous referees who provided her with really valuable and constructive remarks which were very helpful when preparing the final version of this work.  ... 
doi:10.1007/978-3-642-03281-3_8 fatcat:eqdy77qtljhidokzvl2o4a444m

Research on Sports Training Decision Support System Based on Improved Association Rules Algorithm

Linhai Shao, Chi-Hua Chen
2021 Security and Communication Networks  
Finally, according to user input, select the corresponding model and combine with the rules in the knowledge base to generate a reasonable exercise training plan.  ...  First, we introduced a network security method and designed a sports training decision support system based on network security.  ...  Acknowledgments is article was supported by Science and Technology Innovation Project for postgraduates of Mudanjiang Normal University in 2020.  ... 
doi:10.1155/2021/5561970 fatcat:fwzjo5ukybe4lbf5iwiaw6k4im

The Discovery of Discrimination [chapter]

Dino Pedreschi, Salvatore Ruggieri, Franco Turini
2013 Studies in Applied Philosophy, Epistemology and Rational Ethics  
Discrimination discovery from data consists in the extraction of discriminatory situations and practices hidden in a large amount of historical decision records.  ...  We discuss the challenging problems in discrimination discovery, and present, in a unified form, a framework based on classification rules extraction and filtering on the basis of legally-grounded interestingness  ...  An association rule is an expression X → Y, where X and Y are disjoint itemsets. X is called the premise and Y is called the consequence of the association rule.  ... 
doi:10.1007/978-3-642-30487-3_5 dblp:series/sapere/PedreschiRT13 fatcat:iq46kgkbbna3noupira54za3qq

Mining risk patterns in medical data

Jiuyong Li, Ada Wai-chee Fu, Hongxing He, Jie Chen, Huidong Jin, Damien McAullay, Graham Williams, Ross Sparks, Chris Kelman
2005 Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05  
The method has been applied to a real world data set to find patterns associated with an allergic event for ACE inhibitors. The algorithm has generated some useful results for medical researchers.  ...  We study an anti-monotone property for mining optimal risk pattern sets and present an algorithm to make use of the property in risk pattern discovery.  ...  This research has been supported by the RGC Earmarked Research Grant of HKSAR CUHK 4179/01E, the Innovation and Technology Fund (ITF) in the HKSAR [ITS/069/03], and ARC DP0559090.  ... 
doi:10.1145/1081870.1081971 dblp:conf/kdd/LiFHCJMWSK05 fatcat:ifza7fjddfc2tpqkw4av2klpsy

A Brief Overview of Rule Learning [chapter]

Johannes Fürnkranz, Tomáš Kliegr
2015 Lecture Notes in Computer Science  
The two main research directions are descriptive rule learning, with the goal of discovering regularities that hold in parts of the given dataset, and predictive rule learning, which aims at generalizing  ...  In this paper, we provide a brief summary of elementary research in rule learning.  ...  Acknowledgment Tomáš Kliegr was partly supported by the Faculty of Informatics and Statistics, University of Economics, Prague within "long term institutional support for research activities" scheme and  ... 
doi:10.1007/978-3-319-21542-6_4 fatcat:eiyersvgjjakpjpany7db7bcxi

Mining useful patterns

Jiawei Han
2010 Proceedings of the ACM SIGKDD Workshop on Useful Patterns - UP '10  
strong associations between frequent patterns (conjunctions of attribute-value pairs) and class labels Classification: Based on evaluating a set of rules in the form of P 1 ^ p 2 …^ p l "A class = C"  ...  The rule is accepted only if a statistical test (e.g., Z-test) confirms the inference with high confidence Subrule: highlights the extraordinary behavior of a subset of the pop. of the 20 interestingness  ...  The tightness of a group of nodes is the support of a frequent pattern Use Patterns ("Bag of Words") in Image Retrieval Independent features Histogram representation Future of Pattern Mining Mining  ... 
doi:10.1145/1816112.1816113 fatcat:frwef6mttzbsfb672y2wj7dbpi

An Efficient Discrimination Prevention and Rule Protection Algorithms Avoid Direct and Indirect Data Discrimination in Web Mining

Mylam Babu, Sankaralingam Pushpa
2018 International Journal of Intelligent Engineering and Systems  
Indirect discrimination contains a set of rules or techniques which are not explicitly specifying discriminatory features, deliberately or accidentally and could create unfair decisions.  ...  In EDPRP, the discrimination prevention model is based on partial data sets as part of the automated decision making.  ...  In [15] designed statistical method to analyze the quality rule of the apriori algorithm in association rule mining for splitting the interesting rules within massive association rules.  ... 
doi:10.22266/ijies2018.0831.21 fatcat:txpjeqrtmzdmfj46kzuk6gjvru

Recognition Technology of Money Laundering Transactions Based on Data Mining

Lei WU
2018 DEStech Transactions on Economics Business and Management  
Data mining is a common tool for monitoring anti-money laundering transactions.  ...  The article lists several of their common methods, points out their strengths and weaknesses, and introduces the applicable conditions of each method.  ...  The essence of data mining based the association rules is to find the association rules whose support and confidence is over or equal to the minimum support and confidence provided by the user.  ... 
doi:10.12783/dtem/eced2018/23940 fatcat:zsi66or4abhszgnv5lvclexkki

A Rule-Based Clinical Decision Model to Support Interpretation of Multiple Data in Health Examinations

Kuan-Liang Kuo, Chiou-Shann Fuh
2009 Journal of medical systems  
The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users.  ...  This paper proposes a clinical decision support system to assist solving above problems.  ...  Acknowledgement We thank the staff of the Health Evaluation and Promotion Center, Ren-Ai Branch of Taipei City Hospital for their assistance in this research.  ... 
doi:10.1007/s10916-009-9413-3 pmid:20703517 fatcat:2dfmnxns5jhtzc6p476h3tda2e

An intelligent PE-malware detection system based on association mining

Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye, Qingshan Jiang
2008 Journal in Computer Virology  
IMDS is an integrated system consisting of three major modules: PE parser, OOA rule generator, and rule based classifier.  ...  Data mining methods such as Naive Bayes and Decision Tree have been studied on small collections of executables.  ...  Associative classifier For OOA rule generation, we use the OOA_Fast_FP-Growth algorithm to obtain all the association rules with certain support and confidence thresholds, and two objectives: Obj 1 = (  ... 
doi:10.1007/s11416-008-0082-4 fatcat:ni67o6rvzzazfffh7ppyr6775a

DCUBE

Salvatore Ruggieri, Dino Pedreschi, Franco Turini
2010 Proceedings of the 2010 international conference on Management of data - SIGMOD '10  
The SIGMOD attendees will freely pose complex discrimination analysis queries over the database of extracted classification rules, once they are presented with the database relational schema, a few adhoc  ...  Discrimination discovery in databases consists in finding unfair practices against minorities which are hidden in a dataset of historical decisions.  ...  Classification and association rules for discrimination discovery are extracted from a dataset of historical decision records, namely a database table with attributes used for a decision and the decision  ... 
doi:10.1145/1807167.1807298 dblp:conf/sigmod/RuggieriPT10 fatcat:xzuggmiccngwzc4u3jbpwnwcxe

Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods

Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang
2018 Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)  
We demonstrate that a rule-based, a feature-rich, and a neural coreference system all link gendered pronouns to pro-stereotypical entities with higher accuracy than anti-stereotypical entities, by an average  ...  difference of 21.1 in F1 score.  ...  Acknowledgement This work was supported in part by National Science Foundation Grant IIS-1760523, two NVIDIA GPU Grants, and a Google Faculty Research Award.  ... 
doi:10.18653/v1/n18-2003 dblp:conf/naacl/ZhaoWYOC18 fatcat:lxiwqlexjzba7aa7r4mtu7hj4i

An Efficient Algorithm for Mining Coherent Association Rules

Sharada Narra, Siva Ponugoti, Suresh Mullapudi, Madhavi Dabbiru
2014 International Journal of Computer Applications  
Mining association rules without minimum support threshold is an important approximation of the association rule mining problem, which has been recently proposed [1] .In this approach rules are generated  ...  There are many data mining techniques for finding association rules with the predefined minimum support from transaction databases.  ...  ACKNOWLEDGEMENTS Our thanks to Prof.Ch.Suresh and Director (R&D) Dr.K.V.S.V.N Raju for many helpful suggestions and comments in this work.  ... 
doi:10.5120/16769-6336 fatcat:qgkyoio53jdjriq2ktkfodmnci
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