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Privacy Preserving Data Anonymization of Spontaneous ADE Reporting System Dataset

Wen-Yang Lin, Duen-Chuan Yang, Jie-Teng Wang
2015 Proceedings of the ACM Ninth International Workshop on Data and Text Mining in Biomedical Informatics - DTMBIO '15  
Although much work has been done on PPDP, very few studies have focused on protecting privacy of SRS data and none of the anonymization methods is favorable for SRS datasets, due to which contain some  ...  We also conducted experiments to inspect the impact of anonymized data on the strengths of discovered ADR signals.  ...  Availability of data and materials  ... 
doi:10.1145/2811163.2811176 dblp:conf/cikm/LinYW15 fatcat:5de463arrfgjpg4uu2acezbnwy

Signal Detection in Pharmacovigilance: A Review of Informatics-driven Approaches for the Discovery of Drug-Drug Interaction Signals in Different Data Sources

Heba Ibrahim, A. Abdo, Ahmed M. El Kerdawy, A. Sharaf Eldin
2021 Artificial Intelligence in the Life Sciences  
In this article, we review informatics-driven approaches applied by authors focusing on DDI signal detection using different data sources.  ...  Signals can be detected from different data sources such as spontaneous reporting system, scientific literature, biomedical databases and electronic health records.  ...  Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this review paper  ... 
doi:10.1016/j.ailsci.2021.100005 fatcat:m324w243gfflxpiyq3g2qt7znq

Maximizing information through multiple kernel-based heterogeneous data integration and applications to ovarian cancer

Jaya Thomas, Lee Sael
2016 Proceedings of the Sixth International Conference on Emerging Databases Technologies, Applications, and Theory - EDB '16  
In this paper, we introduce a multiple kernel based pipeline for integrative analysis of highthroughput molecular and clinical data. We apply the pipeline on Ovarian cancer data from TCGA.  ...  Recent studies show that utilizing such diverse data results in more accurate predictions. The major challenge faced is how to utilize such diverse data sets in an effective way.  ...  In Proceedings of the 8th International Workshop on Data and Text Mining in Biomedical Informatic -DTMBIO'14.  ... 
doi:10.1145/3007818.3007831 dblp:conf/edb/ThomasS16 fatcat:mrddevuu7zhthjmmlvorskd4hu

2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor

Myeong-Sang Yu, Jingyu Lee, Yongmin Lee, Dokyun Na
2020 BMC Bioinformatics  
, specificity of 0.998, and overall accuracy of 0.981 in 10-fold cross-validation.  ...  However, the models were constructed based on limited numerical features such as molecular descriptors and fingerprints.  ...  About this Supplement This article has been published as part of BMC Bioinformatics, Volume 21 Supplement 5, 2020: Proceedings of the 13th International Workshop on Data and Text Mining in Biomedical Informatics  ... 
doi:10.1186/s12859-020-03588-1 pmid:33106158 fatcat:6r7vst5rfnfdve3olhik5h7dwa

Context-aware multi-token concept recognition of biological entities

Kwangmin Kim, Doheon Lee
2021 BMC Bioinformatics  
Conclusions We expect that our model can be utilized for effective concept recognition and variety of natural language processing tasks on bioinformatics.  ...  Background Concept recognition is a term that corresponds to the two sequential steps of named entity recognition and named entity normalization, and plays an essential role in the field of bioinformatics  ...  About this supplement This article has been published as part of BMC Bioinformatics Volume 22 Supplement 11 2021: Proceedings of the 14th International Workshop on Data and Text Mining in Biomedical Informatics  ... 
doi:10.1186/s12859-021-04248-8 pmid:34674631 fatcat:7cukl5nn4bdkdpvpj3dcz6y4ie

Is automatic detection of hidden knowledge an anomaly?

Judita Preiss
2019 BMC Bioinformatics  
Conclusion: We apply one-class SVM and isolation forest anomaly detection algorithms to a set of hidden connections to rank connections by identifying outlying (interesting) ones and show that the approach  ...  Results: Two experiments are conducted: (1) to avoid errors arising from incorrect extraction of relations, the hypothesis is validated using manually annotated relations appearing in a thesaurus, and  ...  Availability of data and materials Not applicable.  ... 
doi:10.1186/s12859-019-2815-4 fatcat:7szr476obnhhxmao56hrknuidy

Improving Event Detection with Abstract Meaning Representation

Xiang Li, Thien Huu Nguyen, Kai Cao, Ralph Grishman
2015 Proceedings of the First Workshop on Computing News Storylines   unpublished
The workshop aimed to bring together researchers from different communities working on representing and extracting narrative structures in news, a text genre which is highly used in NLP but which has received  ...  The majority of the previous work on narratives and narrative structures have mainly focused on the analysis of fictitious texts.  ...  Acknowledgments We'd like to thank the Georgetown Department of Linguistics for continued support, Amir Zeldes and Nate Chambers for feedback and discussions on components of this work, and the peer reviewers  ... 
doi:10.18653/v1/w15-4502 fatcat:tliiwupbrnhx3bcevyswknwlhm