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Data Analytics and Mining in Healthcare with Emphasis on Causal Relationship Mining

2019 International journal of recent technology and engineering  
Data mining and data analytics have been playing an important role in extracting useful information from healthcare and related data sources.  ...  The dominant functionality of data mining is classification which has been in use in mining healthcare data.  ...  Text mining Finding useful and quality results from text data is called text data mining.  ... 
doi:10.35940/ijrte.d6492.118419 fatcat:zkzif7glbvawhmqualnehr7se4

Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey

Wajid Ali, Wanli Zuo, Rahman Ali, Xianglin Zuo, Gohar Rahman
2021 Applied Sciences  
Causality (cause-effect relations) serves as an essential category of relationships, which plays a significant role in question answering, future events predication, discourse comprehension, decision making  ...  Among them, causality mining (CM) from textual data has become a significant area of concern and has more attention from researchers.  ...  Three distinct methods are used to get related texts for a given causality candidate from 4 billion web pages as a source of BK, including (1) Why-question answering, (2) Using Binary Pattern (BP), and  ... 
doi:10.3390/app112110064 fatcat:btv66da5x5a73auogv5d3lp2bi

Opinion Mining [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
Synonyms Instance language Definition The observation language used by a machine learning system is the language in which the observations it learns from are described.  ...  There are many possible ways an experiment can skew the number of visitors to one variant or another, and many of them will cause a large bias in the treatment effect.  ...  For a large number of experts, the loss bound of the weighted majority algorithm is still interesting since it scales only logarithmically with the number of experts.  ... 
doi:10.1007/978-1-4899-7687-1_100511 fatcat:oluapsjgxzh6nlkqujjj562lzi

Naranjo Question Answering using End-to-End Multi-task Learning Model

Bhanu Pratap Singh Rawat, Fei Li, Hong Yu
2019 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '19  
question answering set used by domain experts for ADR causality assessment.  ...  In this study, we present the first attempt to automatically infer the causality between a drug and an ADR from electronic health records (EHRs) by answering the Naranjo questionnaire, the validated clinical  ...  This work was supported by the grant HL125089 from the National Institutes of Health (NIH). The contents of this paper do not represent the views of NIH.  ... 
doi:10.1145/3292500.3330770 pmid:31799022 pmcid:PMC6887102 fatcat:nf2c33dhzndpnn5q3ojpy3efyu

Argument Mining: A Survey

John Lawrence, Chris Reed
2019 Computational Linguistics  
This paper explores the techniques that establish the foundations for argument mining, provides a review of recent advances in argument mining techniques, and discusses the challenges faced in automatically  ...  Argument Mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language.  ...  Conclusion: A is true (false). with the associated critical questions: 1. Expertise Question: How credible is E as an expert source? 2. Field Question: Is E an expert in the field F that A is in?  ... 
doi:10.1162/coli_a_00364 fatcat:vpnimzg47vdrlaexcqngdat2n4

Mining clinical relationships from patient narratives

Angus Roberts, Robert Gaizauskas, Mark Hepple, Yikun Guo
2008 BMC Bioinformatics  
Conclusion: We have shown that it is possible to extract important clinical relationships from text, using supervised statistical ML techniques, at levels of accuracy approaching those of human annotators  ...  Given the importance of relation extraction as an enabling technology for text mining and given also the ready adaptability of systems based on our supervised learning approach to other clinical relationship  ...  MENELAS [14] also used a full parse, a conceptual representation of the text, and a large scale knowledge base.  ... 
doi:10.1186/1471-2105-9-s11-s3 pmid:19025689 pmcid:PMC2586752 fatcat:3xrbc3ueg5esfm4evwk334r7wm

Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance [article]

Scott Alexander Malec, Elmer Victor Bernstam, Peng Wei, Trevor Cohen, Richard David Boyce
2020 medRxiv   pre-print
For our knowledge-base, we use SemMedDB, a database of computable knowledge mined from the biomedical literature.  ...  to more accurately estimate causal effects.  ...  Unfortunately, since such expertise cannot scale to all available human knowledge, it is infeasible to rely solely on human experts.  ... 
doi:10.1101/2020.07.08.20113035 fatcat:symhqu3l25ayjdoxy457del6jq

From Data Mining to Knowledge Mining [chapter]

Kenneth A. Kaufman, Ryszard S. Michalski
2005 Handbook of Statistics  
The effective use of background as well as previously created knowledge in reasoning about new data makes it possible for the knowledge mining system to derive useful new knowledge not only from large  ...  The second part outlines a multistrategy methodology for an emerging research direction, called knowledge mining, by which we mean the derivation of high-level concepts and descriptions from data through  ...  as humans can, and produce a causal explanation why these dependencies exist.  ... 
doi:10.1016/s0169-7161(04)24002-0 fatcat:romqi4ngpfd5vkxeawvb62n7pi

Text Mining for Drug–Drug Interaction [chapter]

Heng-Yi Wu, Chien-Wei Chiang, Lang Li
2014 Msphere  
Biomedical Text Mining-Text mining refers to the process of deriving highquality information from text, which relies on NLP.  ...  DDI text mining tools for PK data collection from the literature and data integration from multiple databases.  ...  This method needs laborious efforts to define grammars or rules, and text in training dataset is manually tagged by a human expert.  ... 
doi:10.1007/978-1-4939-0709-0_4 pmid:24788261 pmcid:PMC4636907 fatcat:jdxhh37g2zer3n4gikt34ewkry

Mining Electronic Health Records: A Survey [article]

Pranjul Yadav, Michael Steinbach, Vipin Kumar, Gyorgy Simon
2017 arXiv   pre-print
Mining EHRs could lead to improvement in patient health management as EHRs contain detailed information related to disease prognosis for large patient populations.  ...  Next, we describe major approaches used for EHR mining, the metrics associated with EHRs, and the various study designs.  ...  [White et al. 2013 ] conducted a large scale study for analyzing web search logs for detection of adverse events related to the drug pair, paroxetine and pravastatin.  ... 
arXiv:1702.03222v2 fatcat:aizt3bnmibcc7kv67h6qf7ts7q

Mining Electronic Health Records (EHRs)

Pranjul Yadav, Michael Steinbach, Vipin Kumar, Gyorgy Simon
2018 ACM Computing Surveys  
Mining EHRs could lead to improvement in patient healthcare management as EHRs contain detailed information related to disease prognosis for large patient populations.  ...  Next, we describe major approaches used for EHR mining, the metrics associated with EHRs, and the various study designs.  ...  [138] conducted a large scale study for analyzing web search logs for detection of adverse events related to the drug pair, paroxetine and pravastatin.  ... 
doi:10.1145/3127881 fatcat:xil7qev3xbf3pmfv5vtak4f2jq

Open challenges for data stream mining research

Georg Krempl, Myra Spiliopoulou, Jerzy Stefanowski, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi
2014 SIGKDD Explorations  
We aim to provide a comprehensive statistical overview of Tumblr and compare it with other popular social services, including blogosphere, Twitter and Facebook, in answering a couple of key questions:  ...  This work serves as an early snapshot of Tumblr that later work can leverage.  ...  to thank the participants of the RealStream2013 workshop at ECMLPKDD2013 in Prague, and in particular Bernhard Pfahringer and George Forman, for suggestions and discussions on the challenges in stream mining  ... 
doi:10.1145/2674026.2674028 fatcat:y3bozzeohveibgxb5wmiwfcogm

Cost-to-Go Function Approximation [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
The COVERING algorithm starts with an empty theory.  ...  Adaptations to the multi-class case are typically performed via class binarization, learning different rule sets for binary problems.  ...  Question answering was another fruitful text-based domain: FAQ-Finder and FA11Q.  ... 
doi:10.1007/978-1-4899-7687-1_100093 fatcat:vse7ncdqs5atlosjhz7fhlj3im

Database Issues in Knowledge Discovery and Data Mining

Chris Rainsford, John Roddick
1999 Australasian Journal of Information Systems  
Data mining is useful in situations where the volume of data is either too large or too complicated for manual processing or, to a lesser extent, where human experts are unavailable to provide knowledge  ...  This paper surveys, from the standpoint of the database systems community, current issues in data mining research by examining the architectural and process models adopted by knowledge discovery systems  ...  In situations where human experts are unavailable knowledge bases can be constructed from data sets. Automatically discovered rules can also be used to verify rules proposed by human experts.  ... 
doi:10.3127/ajis.v6i2.310 fatcat:57zzkqzw2bdgndhjp5tumgicd4

Measuring the similarity between implicit semantic relations using web search engines

Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka
2009 Proceedings of the Second ACM International Conference on Web Search and Data Mining - WSDM '09  
For example, consider the situation where you know an entity-pair (e.g.  ...  We then present an efficient clustering algorithm to cluster the extracted lexical patterns. Finally, we measure the relational similarity between word-pairs using inter-cluster correlation.  ...  Bootstrapping methods [19, 4] that require a small number of seeds (ca. 10 pairs of instances per relation) have been successfully used to extract a large number of candidate instance-pairs from a text  ... 
doi:10.1145/1498759.1498815 dblp:conf/wsdm/BollegalaMI09 fatcat:yh6zo5euevcxnkpmhfx5lbqtd4
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