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EXTRACTION OF GENE-DISEASE RELATIONS FROM MEDLINE USING DOMAIN DICTIONARIES AND MACHINE LEARNING
2005
Biocomputing 2006
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We constructed a dictionary for disease and gene names from six public databases and extracted relation candidates by dictionary matching. ...
We describe a system that extracts disease-gene relations from M edLine. ...
We could safely regard co-occurrences as containing correct relations if candidate disease and gene names were considered to be correct. ...
doi:10.1142/9789812701626_0002
fatcat:w5kyfvessndrzautvqekzkjnfu
A Short Survey of Biomedical Relation Extraction Techniques
[article]
2017
arXiv
pre-print
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In the current research, we focus on different aspects of relation extraction techniques in biomedical domain and briefly describe the state-of-the-art for relation extraction between a variety of biological ...
Biomedical information is growing rapidly in the recent years and retrieving useful data through information extraction system is getting more attention. ...
[12] have applied a supervised machine learning method that detects and classifies relations between diseases and treatments extracted from PubMed abstracts and between genes and diseases in human GeneRIF ...
arXiv:1707.05850v3
fatcat:snyvtomcxbbeplkspqaucmpely
Application of Biomedical Text Mining
[chapter]
2018
Artificial Intelligence - Emerging Trends and Applications
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Using the information will help understand the mechanism of disease generation, promote the development of disease diagnosis technology, and promote the development of new drugs in the field of biomedical ...
This chapter emphasizes the two aspects in biomedical text mining involving static biomedical information recognization and dynamic biomedical information extraction using instance analysis from our previous ...
First, the approach identified genes and drugs entities from Medline abstract; the second step is to extract different levels of gene-2-drug pairs. ...
doi:10.5772/intechopen.75924
fatcat:5o27ptssi5fwzbelnpktkwplby
A Framework for Extracting Biological Relations from Different Resources
2015
International Journal of Computer Applications
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Manually extracting biological relations from published literature and transforming them into machine-understandable knowledge is a difficult task because biological domain comprises huge, dynamic, and ...
The results has showed that different relations can be extracted such as gene-disease, protein-protein. ...
Additional pairs have been extracted from MEDLINE using the learned patterns. ...
doi:10.5120/21044-3675
fatcat:u5neftbmmngrrpzlany6ssiy2y
Text analytics for life science using the Unstructured Information Management Architecture
2004
IBM Systems Journal
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Acknowledgments BioTeKS is in large part a systems integration effort that builds on technologies and expertise developed ...
The second approach to entity extraction is based on rules, not enumeration, where the rules can be developed by domain experts, either directly or by using machine-learning methods. ...
The BioTeKS team is also exploring machine learning (ML) approaches to entity extraction. ...
doi:10.1147/sj.433.0490
fatcat:altfinouzbdy7mrcqx2kzdzecy
BioMap
2004
Proceedings of the 2004 ACM symposium on Applied computing - SAC '04
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The overall goal of this work is to investigate and develop a complete knowledge base, called BioMap, using the entire MEDLINE collection of (over 12 million) bibliographic citations and author abstracts ...
Knowledge, in this case, is defined as one-to-many and many-to-many relationships among biological entities such as gene, protein, drug, disease, etc. ...
The Indiana Genomics Initiative (INGEN) of Indiana University is supported in part by Lilly Endowment Inc. ...
doi:10.1145/967900.967927
dblp:conf/sac/KumarPMSL04
fatcat:2usbpchpzbfadlrhki5ionnqqu
Disease Named Entity Recognition by Machine Learning Using Semantic Type of Metathesaurus
2013
International Journal of Machine Learning and Computing
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The corpus was obtained from MEDLINE 2001 and contains 3655 annotated sentences. To extract the concepts from sentences we used semantic types of UMLS metathesaurus. ...
Algorithm for extracting concept from sentence and generate the binary concept feature for machine learning. ...
doi:10.7763/ijmlc.2013.v3.367
fatcat:cmotpq52yzgvxfpocecggea7n4
Drug Disease Relation Extraction from Biomedical Literature Using NLP and Machine Learning
2021
Mobile Information Systems
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These features are manipulated to pinpoint the relations between drug and disease. The proposed approach was evaluated using a standard corpus extracted from MEDLINE. ...
These relations can be extracted from biomedical literature available on various databases. This study examines the extraction of semantic relations that can occur between diseases and drugs. ...
Acknowledgments e authors would like to acknowledge the support of Taif University Researchers Supporting Project (no. TURSP-2020/292), Taif University, Taif, Saudi Arabia. ...
doi:10.1155/2021/9958410
doaj:8ef39a03dd8a47968219ca1fd1f38c65
fatcat:vt3fcxqsb5ahnkytwvrwivougq
Best Treatment Identification for Disease Using Machine Learning Approach in Relation to Short Text
2014
IOSR Journal of Computer Engineering
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The goal of Machine Learning is to construct a computer system that can adapt and learn from their experience. ...
Our main aim is to integrate machine learning in medical field and build an application that is capable of automatically identifying and disseminating disease and treatment related information, further ...
Machine Learning has emerged as an important technology almost in all domains of scientific research and medical fields. ...
doi:10.9790/0661-16370512
fatcat:jfpysk3kezclnkbzm3sv4kxqbe
Application of Public Knowledge Discovery Tool (PKDE4J) to Represent Biomedical Scientific Knowledge
2018
Frontiers in Research Metrics and Analytics
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Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research. ...
models, and RNN, are used in machine learning approaches. ...
doi:10.3389/frma.2018.00007
fatcat:ypnjhygle5ec5edk7xsxe5kcra
Comparative experiments on learning information extractors for proteins and their interactions
2005
Artificial Intelligence in Medicine
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Conclusion: Our results show that it is promising to use machine learning to automatically build systems for extracting information from biomedical text. ...
Results: We demonstrate that machine learning approaches using support vector machines and maximum entropy are able to identify human proteins with higher accuracy than several previous approaches. ...
Acknowledgements We would like to thank members of the Marcotte lab for helping to tag Medline abstracts. We would also like to thank Kristie Seymore for making the IE-tagging tool available. ...
doi:10.1016/j.artmed.2004.07.016
pmid:15811782
fatcat:rvazhvl7zfcnjp2htqsro6vo7e
A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature
2018
AMIA Annual Symposium Proceedings
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In this work, we show that there is a large number of mutations that are missed by using this standard approach. ...
As the cost of DNA sequencing continues to fall, an increasing amount of information on human genetic variation is being produced that could help progress precision medicine. ...
Annotation guidelines The domain of interest in our work is colorectal cancer, which was used to help define a subset of citations from MEDLINE R for annotation. ...
pmid:30815103
pmcid:PMC6371299
fatcat:u5q5labhtvgi3drzr4pqjsmygy
Biomedical text mining and its applications in cancer research
2013
Journal of Biomedical Informatics
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The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. ...
We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining ...
[42] could extract gene-disease relations from Medline. ...
doi:10.1016/j.jbi.2012.10.007
pmid:23159498
fatcat:xd7j77sbwfhklkat6tael64lbq
A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature
[article]
2018
bioRxiv
pre-print
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In this work, we show that there is a large number of mutations that are missed by using this standard approach. ...
As the cost of DNA sequencing continues to fall, an increasing amount of information on human genetic variation is being produced that could help progress precision medicine. ...
Annotation guidelines The domain of interest in our work is colorectal cancer, which was used to help define a subset of citations from MEDLINE R for annotation. ...
doi:10.1101/363473
fatcat:ic4iss7rpfaizgea46e5caworq
A knowledge-driven conditional approach to extract pharmacogenomics specific drug–gene relationships from free text
2012
Journal of Biomedical Informatics
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In this study, we have developed a conditional relationship extraction approach to extract PGx-specific drug-gene pairs from 20 million MEDLINE abstracts using known drug-gene pairs as prior knowledge. ...
The success of many systematic and integrative computational approaches for PGx studies depends on the availability of accurate, comprehensive and machine understandable drug-gene relationship knowledge ...
Acknowledgments Both Rong Xu and QuanQiu Wang have conceived the idea, designed and implemented the algorithms. Xu has written the paper. ...
doi:10.1016/j.jbi.2012.04.011
pmid:22561026
pmcid:PMC4589154
fatcat:jf7gb3srsjhfjnml7kjy5nhgbu
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