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Identifying Risk Groups Associated with Colorectal Cancer
[chapter]
2006
Lecture Notes in Computer Science
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Association rule discovery, association classification and scalable clustering analysis are applied to the colorectal cancer patients' profiles in contrast to background patients' profiles. ...
In this paper, we explore data mining techniques for the task of identifying and describing risk groups for colorectal cancer (CRC) from population based administrative health data. ...
Acknowledgements The authors acknowledge the Australian Government Department of Health and Ageing and the Queensland Department of Health for providing data for this research. ...
doi:10.1007/11677437_20
fatcat:pl5laha2vrcw7d3yjmqhq5ohdq
Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization
2020
BMC Medical Informatics and Decision Making
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Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem ...
Our pipeline that uses text mining to identify objects and relationships to construct a graph and uses graph-based influence maximization to discover the most influential co-occurring genes presents a ...
We use biomedical literature mining and graph-based influence maximization, and integrated bioinformatics database to identifying influential genes for GI cancers. ...
doi:10.1186/s12911-020-01227-6
pmid:32883271
fatcat:kuhlzhnfvjczrn3vr7sg5cks5y
Heuristic Classifier for Observe Accuracy of Cancer Polyp Using Video Capsule Endoscopy
2017
Asian Pacific Journal of Cancer Prevention
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Methods: Colonoscopy is a technique for examine colon cancer, polyps. In endoscopy, video capsule is universally used mechanism for finding gastrointestinal stages. ...
But both the mechanisms are used to find the colon cancer or colorectal polyp. ...
separates the classes, and only non-zero αi for the decision rule. ...
doi:10.22034/apjcp.2017.18.6.1681
pmid:28670889
pmcid:PMC6373793
fatcat:cfzo2x64lzgbhhodus33v4c3ba
Text mining of cancer-related information: Review of current status and future directions
2014
International Journal of Medical Informatics
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In this article, we provide a critical overview of the current state of the art for TM related to cancer. ...
In addition, there is a need for a comprehensive cancer ontology that would enable semantic representation of textual information found in narrative reports. ...
For example, the CGMIM system for mining information about cancers and associated genes considers 21 major cancer types [55] . ...
doi:10.1016/j.ijmedinf.2014.06.009
pmid:25008281
fatcat:c3ifkrjacjgghdm6kz65flh434
Learning Relational Descriptions of Differentially Expressed Gene Groups
2008
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
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Significant number of discovered groups of genes had a description which highlighted the underlying biological process that is responsible for distinguishing one class from the other classes. ...
This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to find compactly described groups of genes differentially expressed in specific cancers ...
(true positives). 2) Inducing a set of subgroup describing rules: In CN2, for a given class in the rule head, the rule with the best value of the heuristic function found in the beam search is kept. ...
doi:10.1109/tsmcc.2007.906059
fatcat:tpydbrqgqjdudduatpsotov2cm
Subgroup Discovery Techniques and Applications
[chapter]
2005
Lecture Notes in Computer Science
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such as planning a population screening campaign aimed at detecting individuals with high disease risk. ...
Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allow the decision maker to recognize some important relations and to perform an appropriate action, ...
Namely, the best-scoring rule for the lymphoma class in the multi-class cancer recognition problem contains a feature corresponding to a gene routinely used as a marker in diagnosis of lymphomas (CD20) ...
doi:10.1007/11430919_2
fatcat:tuv3nuplf5bg3oora6hbn3fvne
Data mining and CBR integrated methods in medicine: a review
2010
International Journal of Medical Engineering and Informatics
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Nowadays, a large number of data mining (DM) techniques are available for data analysis and prediction in medicine. ...
His research interests are AI and multi-agent system and its application to medicine, e-commerce and semantic web. ...
Two different representations of knowledge, rules and causal structures, are learned. Rules capture interesting patterns and regularities in the database. ...
doi:10.1504/ijmei.2010.031521
fatcat:ond5wvx75vc47pm4f6x6qwd6um
Relevancy in Constraint-Based Subgroup Discovery
[chapter]
2006
Lecture Notes in Computer Science
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the property of interest. ...
The chapter provides a novel interpretation of relevancy constraints and their use for feature filtering, introduces relevancy-based mechanisms for handling unknown values in the examples, and discusses ...
The experiments were performed separately for each cancer class so that a two-class learning problem was formulated for each cancer class as a target. ...
doi:10.1007/11615576_12
fatcat:knr4gldf6naitf5ex3yjf2mksu
Induction of comprehensible models for gene expression datasets by subgroup discovery methodology
2004
Journal of Biomedical Informatics
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Some of the discovered classifiers allow for novel biological interpretations. ...
Finding disease markers (classifiers) from gene expression data by machine learning algorithms is characterized by a high risk of overfitting the data due the abundance of attributes (simultaneously measured ...
Such a Table 6 Rules induced for the multi-class cancer domain for cancer types with 16 (lymphoma and CNS) and 24 (leukemia) target class samples Models for the multi-class cancer domain lymphoma class ...
doi:10.1016/j.jbi.2004.07.007
pmid:15465480
fatcat:ysfzp4ky25ej3mom37b5sy3i6q
Natural Language Processing for EHR-Based Computational Phenotyping
2018
IEEE/ACM Transactions on Computational Biology & Bioinformatics
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Among the surveyed methods, well-designed keyword search and rule-based systems often achieve good performance. ...
However, the construction of keyword and rule lists requires significant manual effort, which is difficult to scale. ...
Acknowledgment This work was supported in part by NIH Grant 1R21LM012618-01, NLM Biomedical Informatics Training Grant 2T15 LM007092-22, and the Intel Science and Technology Center for Big Data. ...
doi:10.1109/tcbb.2018.2849968
pmid:29994486
pmcid:PMC6388621
fatcat:wsksxvr7lfbgjowrsymghld64u
Natural Language Processing for EHR-Based Computational Phenotyping
[article]
2018
arXiv
pre-print
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Among the surveyed methods, well-designed keyword search and rule-based systems often achieve good performance. ...
However, the construction of keyword and rule lists requires significant manual effort, which is difficult to scale. ...
They achieved accuracies of 72%, 78%, and 94% for T, N, and M staging, respectively. Xu et al. [34] implemented a heuristic rule-based approach for colorectal cancer assertion. ...
arXiv:1806.04820v2
fatcat:fo5ck7rpgzhb7dgmqfjc3bdw7y
Data Mining in Employee Healthcare Detection Using Intelligence Techniques for Industry Development
2022
Journal of Healthcare Engineering
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Even in today's environment, when there is a plethora of information accessible, it may be difficult to make appropriate choices for one's well-being. ...
Because the degree of rise in the number of patient roles is directly related to the rate of people growth and lifestyle variations, the healthcare sector has a significant need for data processing services ...
Using Association Rules (AR) and neural networks, Karabatak and Mustafa [15] offered an automated diagnostic technique for diagnosing breast cancer that is based on Association Rules (AR) and neural ...
doi:10.1155/2022/6462657
pmid:35047155
pmcid:PMC8763559
fatcat:hg5tffogtjcejbcwqtjqu2vsfq
Investigating Global Lipidome Alterations with the Lipid Network Explorer
2021
Metabolites
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LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container. ...
It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. ...
Lipidomics of Colorectal Cancer We investigated lipidomics data from Wang et al. [16] about a lipidomics characterization of colorectal cancer patients. ...
doi:10.3390/metabo11080488
fatcat:6anv5a4xzfhm3i4pgzwsdmxe5a
Mining Biomedical Text towards Building a Quantitative Food-Disease-Gene Network
[chapter]
2011
Studies in Computational Intelligence
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and visualization, which integrates the previously extracted relationships and realizes a preliminary user interface for intuitive observation and exploration. ...
To uncover the underlying knowledge base hidden in such data, text mining techniques have been utilized. ...
No significant associations were found between intake Not-related Medium of carotenoids and colorectal cancer risk. search articles on the relationship between "soy" and "cancer", a holistic summary of ...
doi:10.1007/978-3-642-22913-8_10
fatcat:uyt7hnpikjdh5bttlzcng7xkrm
Establishing a baseline for literature mining human genetic variants and their relationships to disease cohorts
2016
BMC Medical Informatics and Decision Making
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The Variome corpus, a small collection of published articles about inherited colorectal cancer, includes annotations of 11 entity types and 13 relation types related to the curation of the relationship ...
Methods: In this paper, we focus on assessing performance on extracting the relations in the corpus, using gold standard entities as a starting point, to establish a baseline for extraction of relations ...
Declarations The publication charges for this article were funded by Next-Generation Information Computing Development Program through the National ...
doi:10.1186/s12911-016-0294-3
pmid:27454860
pmcid:PMC4959367
fatcat:kxniph5j5jbkjfht7q4hxkaisu
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