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Identifying the Leading Factors of Significant Weight Gains Using a New Rule Discovery Method [article]

Mina Samizadeh, Jessica C Jones-Smith, Bethany Sheridan, Rahmatollah Beheshti
2021 arXiv   pre-print
Overweight and obesity remain a major global public health concern and identifying the individualized patterns that increase the risk of future weight gains has a crucial role in preventing obesity and  ...  Through extensive series of experiments, we show new and complementary findings regarding the predictors of future dangerous weight gains.  ...  Conclusion In this study, aiming to identify the most important factors that lead to dangerous weight gains, we generated a series of X → Y (if-then) rules predicting such patterns using a very large longitudinal  ... 
arXiv:2111.04475v1 fatcat:sff3qb4pnfgudkfwceppboptbm

Complex event processing enrichment: Motivations and challenges

Alaa Alakari, Kin Fun Li, Fayez Gebali
2017 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)  
In addition, a cost-gain evaluation measure to determine the best tradeoff to identify a particular SOI is presented.  ...  Therefore, to fine tune the CEP pattern to identify SOI, the following requirements must be met: first, a minimum number of rules must be used to refine the CEP pattern to avoid increased pattern complexity  ...  I would like to express my deep sense of gratitude and profound respect to the following special people who supported me during my Ph.D. journey:  ... 
doi:10.1109/pacrim.2017.8121891 dblp:conf/pacrim/AlakariLG17 fatcat:dhohdleyejegbetjcxnoz53oxu

Competency Discovery System: Integrating the Enhanced ID3 Decision Tree Algorithm to Predict the Assessment Competency of Senior High School Students

Jestoni Vasquez, Benilda Eleonor Comendador
2019 International Journal on Advanced Science, Engineering and Information Technology  
The academic and technical performance is often used for predicting the learning behaviour of the students and can be a crucial factor in building their better future.  ...  The study presents the development of Competency Discovery System, which integrates enhanced Iterative Dichometer 3 (ID3) decision tree algorithm, to predict assessment competency of senior high school  ...  To generate a decision tree, a set of rules and selection factors were applied.  ... 
doi:10.18517/ijaseit.9.1.7763 fatcat:7sloesiwxvftjkanr5kokppxhu

Compact Weighted Class Association Rule Mining Using Information Gain

Syed Ibrahim, Chandran
2011 International Journal of Data Mining & Knowledge Management Process  
Weighted association rule mining reflects semantic significance of item by considering its weight. Classification constructs the classifier and predicts the new data instance.  ...  The weight of the item is considered as one of the parameter in generating the weighted class association rules. This proposed algorithm calculates the weight using the HITS model.  ...  A common rule is defined as x → c, where x is a set of non class attributes and c is class label. The quality measurement factor of a rule is weighted support and weighted confidence.  ... 
doi:10.5121/ijdkp.2011.1601 fatcat:khfgjg55vbbt7k436nhl7hl5iy

Unified Transcriptomic Signature of Arbuscular Mycorrhiza Colonization in Roots of Medicago truncatula by Integration of Machine Learning, Promoter Analysis, and Direct Merging Meta-Analysis

Manijeh Mohammadi-Dehcheshmeh, Ali Niazi, Mansour Ebrahimi, Mohammadreza Tahsili, Zahra Nurollah, Reyhaneh Ebrahimi Khaksefid, Mahdi Ebrahimi, Esmaeil Ebrahimie
2018 Frontiers in Plant Science  
, UNCERTAINTY, GINI INDEX, Chi Squared, RULE, INFO GAIN, and INFO GAIN RATIO.  ...  The AP2 domain class transcription factor, GRAS family transcription factors, and cyclin-dependent kinase were among the highly expressed meta-genes identified in the signature.  ...  This research was supported by use of the Nectar Research Cloud, a collaborative Australian research platform supported by the National Collaborative Research Infrastructure Strategy (NCRIS).  ... 
doi:10.3389/fpls.2018.01550 pmid:30483277 pmcid:PMC6240842 fatcat:quqjsixu35gr3hw37ft26yuzkm

Advances in nuclear magnetic resonance for drug discovery

Robert Powers
2009 Expert Opinion on Drug Discovery  
Objective/Method-A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented.  ...  , NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR.  ...  NMR is also making a significant contribution to the functional assignment of these unannotated proteins to identify new drug discovery targets.  ... 
doi:10.1517/17460440903232623 pmid:20333269 pmcid:PMC2843924 fatcat:hfps6aoma5eiddyowjra6mobne

Application of Big Data Analysis with Decision Treefor Road Accident

Addi Ait-Mlouk, Fatima Gharnati, Tarik Agouti
2017 Indian Journal of Science and Technology  
Objectives: In transportation field, a huge amount of data collected by IoT systems, remote sensing and other data collection tools brings new challenges, the size of this data becomes extremely big and  ...  This work employed large-scale machine learning techniques especially Decision Tree with Apache Spark framework for big data analysis to build a model that can predict the factors lead to road accidents  ...  Knowledge Discovery in Big Data Decision Tree (DT) DT learning is a powerful method for pattern categorizations 28 .  ... 
doi:10.17485/ijst/2017/v10i29/117325 fatcat:ygddvftm2fgv5oe65dmnhwrxke

Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence?

Edward J. Griffen, Alexander G. Dossetter, Andrew G. Leach, Shane Montague
2018 Drug Discovery Today  
http://researchonline.ljmu.ac.uk/id/eprint/8484/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively.  ...  Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence?  ...  Using this method, the more evidence (number of examples) that a rule has, the lower the frequency of a given direction is needed for it to pass statistical significance.  ... 
doi:10.1016/j.drudis.2018.03.011 pmid:29577971 fatcat:vhpkcv5ofrgdhcqrrbtmfkx4na

A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD)

Stefania Pasanisi, Roberto Paiano
2018 Information  
With the use of the K-means algorithm, significant groups of patients are found.  ...  In this paper, we combine Clustering, Association Rules, and Neural Networks for the assessment of heart-event-related risk factors, targeting the reduction of CVD risk.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/info9040090 fatcat:aiwn2vqpgbbp5nvgngjh3jxve4

Gain ratio based fuzzy weighted association rule mining classifier for medical diagnostic interface

N S NITHYA, K DURAISWAMY
2014 Sadhana (Bangalore)  
It used a ranking based weight value to identify the potential attribute. When we take a large number of distinct values, the computation of information gain value is not feasible.  ...  The health care environment still needs knowledge based discovery for handling wealth of data. Extraction of the potential causes of the diseases is the most important factor for medical data mining.  ...  The WEKA (Quinlan 1986 ) classifier package has its own version of C4.5 known as J4.8. We have used J4.8 to identify the significant attributes.  ... 
doi:10.1007/s12046-013-0198-1 fatcat:lbjiozvforfgfe3e4raku2fcra

Specificity Enhancement in microRNA Target Prediction through Knowledge Discovery [chapter]

Yanju Zhang, Jeroen S. de Bruin, Fons J.
2010 Machine Learning  
Erno Vreugdenhil for discussing some biological implications of the results and Peter van de Putten for suggestions on the use of WEKA.  ...  This research has been partially supported by the BioRange program of the Netherlands BioInformatics Centre (BSIK grant).  ...  Using Max coverage as a cutoff criterion, we obtained that all the rules have the max significance lower than 8.  ... 
doi:10.5772/9140 fatcat:gedflwuorjdvtgrcmhgs2534lq

Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned

Nada Lavrač, Bojan Cestnik, Dragan Gamberger, Peter Flach
2004 Machine Learning  
Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allows the decision maker to recognize some important relations and to perform an appropriate action,  ...  Different subgroup discovery approaches are outlined, and their advantages over using standard classification rule learning are discussed.  ...  One of the heuristics appropriate for subgroup discovery is the weighted relative accuracy heuristic used in this work which trades off the generality of a rule ( p(Cond), i.e., rule coverage) and its  ... 
doi:10.1023/b:mach.0000035474.48771.cd fatcat:lvv46jbfrffllkyrrlk2hrapvm

Hit discovery and hit-to-lead approaches

György M. Keserű, Gergely M. Makara
2006 Drug Discovery Today  
Development of quality leads using hit confirmation and hit-to-lead approaches present their own challenges, depending on the hit discovery method used to identify the initial hits.  ...  Several factors are easier to control in fragment-based lead discovery because the number of samples is significantly smaller than that used for HTS.  ... 
doi:10.1016/j.drudis.2006.06.016 pmid:16846802 fatcat:7j77tdf22bhl5catysavd2rixa

Page 500 of ASQ World Conference on Quality and Improvement Proceedings Vol. 42, Issue [page]

1988 ASQ World Conference on Quality and Improvement Proceedings  
With regard to the gain in knowledge from a classical experiment, new discoveries are really only related to the specific factor of interest that is being scrutinized.  ...  The classical experimentation method consists of varying one factor at a time and determining the significance of that factor.  ... 

Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

Samson Olaitan Oselusi, Alan Christoffels, Samuel Ayodele Egieyeh
2021 Molecules  
Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.  ...  The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens.  ...  Some of the methods reviewed here have been used to identify new therapeutic interventions against various pathogens, such as the inhibitors of matrix protein (VP40) in Ebola virus [12] .  ... 
doi:10.3390/molecules26133970 pmid:34209681 fatcat:lzndtgfbhza4lfb26cadcio47y
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