PPT-A Method for Mining Infrequent Causal Associations and Its

Abstract In many realworld applications it is important to mine causal relationships where an event or event pattern causes certain outcomes with low probability Discovering this kind of causal relationships can help us prevent or correct negative outcomes caused by their antecedents In this paper we propose an innovative data mining framework and apply it to mine potential causal associations in electronic patient data sets where the drugrelated events of interest occur infrequently Specifically we created a novel interestingness measure exclusive causalleverage based on a computational fuzzy recognitionprimed decision RPD model that we previously developed On the basis of this new measure a data mining algorithm was developed to mine the causal relationship between drugs and their associated adverse drug reactions ADRs . Jean-Philippe Pellet. Andre . Ellisseeff. Presented by Na Dai. Motivation. Why structure . l. earning?. What are Markov blankets?. Relationship between feature selection and Markov blankets?. Previous work. Ognyan. Oreshkov. , . Fabio . Costa. , . ČaslavBrukner. Bhubaneswar. arXiv:1105.4464. 20 December2011. Conference on Quantum Information. X. T. D. E. A. B. C. A. B. C. D. E. Measurements in space-time. Ognyan. Oreshkov. , . Fabio . Costa. , . ČaslavBrukner. Bhubaneswar. arXiv:1105.4464. 20 December2011. Conference on Quantum Information. X. T. D. E. A. B. C. A. B. C. D. E. Measurements in space-time. from . Mass Cytometry Data. Presenters: . Ioannis Tsamardinos. and Sofia Triantafillou. Institute of Computer Science, Foundation for Research and Technology, Hellas. Computer Science Department, University of Crete. Michael Rosenblum. March 16, 2010. Overview. I describe the set of assumptions encoded by a causal directed acyclic graph (DAG). I use an example from page 15 of the book . Causality. by Judea Pearl (2009). . PcOR. : . controversies in the field. Heejung Bang, PhD. UC-Davis. 1. Why PCOR?. Me as . a . negative/null/lazy researcher-patient. . & co-I of a PCORI trial, my personal and honest feelings about . Ling . Ning. &. . Mayte. . Frias. . Senior Research Associates. Neil . Huefner. . Associate Director. Timo. Rico. Executive Director. Outline. Understanding causal effects. Methods for estimating causal effects. Dr Steven Stillman. Senior Fellow, Motu . Adjunct Professor of Economics, Waikato. NIDEA Theme Leader, New Zealand’s individuals, families and households. Launch Symposium, November 24. th. 2010. The Importance of Experimental Evidence . Naftali Weinberger. Tilburg Center for Logic, Ethics and Philosophy of Science. Time and Causality in the Sciences. June 8. th. , 2017. Principle of the . C. ommon Cause. iPad. Happiness. iPad. Happiness. Causes are . difference-makers. .. Effect need not be . universal/deterministic. .. N. ot . everyone who is bitten by a cobra . dies. .. N. ot . everyone who dies is bitten by a . cobra. .. B. ut . cobra bites still cause . Presented by: Arvind Kouta. 1. Consistency Models. Strict Consistency: operations are executed in order of wall-clock time (NTP). Sequential Consistency: operations are executed in some global ordering (Total Ordering). : A Mechanist Perspective. Stuart Glennan. Butler . University. The singularist and generalist view of causation. The. generalist view: Particular events are causally related because they fall under general laws. : A Mechanist Perspective. Stuart Glennan. Butler . University. The singularist and generalist view of causation. The. generalist view: Particular events are causally related because they fall under general laws. Qiang . Ning, . . Zhili. . Feng. , . Hao Wu, . Dan . Roth. 07/18/2018. University of Illinois, . Urbana-Champaign . &. University . of Pennsylvania. Time is Important. Understanding .