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adr-prediction specifications

Information


Unique identifier OMICS_20398
Name adr-prediction
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Medium
Stability Stable
Maintained Yes

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Maintainers


  • person_outline Emir Munoz
  • person_outline Emir Munoz

Publication for adr-prediction

adr-prediction citations

 (9)
library_books

Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records

2017
Sci Rep
PMCID: 5703951
PMID: 29180758
DOI: 10.1038/s41598-017-16674-x

[…] correct prediction of edges in category 2 does not directly contribute to patient care, but as these databases are widely used for research purposes it is valuable to detect missing information., adr prediction has been the subject of numerous previous publications, which have been reviewed thoroughly,. existing approaches can be subdivided into two key objectives. firstly, to predict adrs […]

library_books

Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records

2017
PMCID: 5635478
PMID: 29090077
DOI: 10.1155/2017/7575280

[…] postmarketing surveillance with a large amount of population is necessary for remaining adr monitoring. to this end, there are two multidisciplinary tasks of adr surveillance: adr identification and adr prediction. the former task targets on retrieval of unrecognized adr that may exist in data but not explicitly described as knowledge, while the latter one aims to construct a model […]

library_books

Predicting neurological Adverse Drug Reactions based on biological, chemical and phenotypic properties of drugs using machine learning models

2017
Sci Rep
PMCID: 5429831
PMID: 28408735
DOI: 10.1038/s41598-017-00908-z

[…] properties with their target profiles. zhang et al. used ensemble methods and devised feature selection based multi-label k-nearest neighbour method (fs-mlknn) using which essential features for adr prediction can be predicted. huang et al. integrated drug information (drug target data and clinical observation data) with network information (protein-protein interaction networks and gene […]

library_books

Prediction of Hospitalization due to Adverse Drug Reactions in Elderly Community Dwelling Patients (The PADR EC Score)

2016
PLoS One
PMCID: 5087856
PMID: 27798708
DOI: 10.1371/journal.pone.0165757

[…] strongest predictor of an adr followed by presence of dementia, renal failure, drug changes in the preceding 3 months and use of anticholinergic medications; these variables were used to derive the adr prediction score. the predictive ability of the score, assessed from calculation of the area under the receiver operator characteristic (roc) curve, was 0.70 (95% confidence interval (ci) […]

library_books

Hospitalization in older patients due to adverse drug reactions –the need for a prediction tool

2016
PMCID: 4859526
PMID: 27194906
DOI: 10.2147/CIA.S99097

[…] multiple risk factors for adrs, ideally, the gps should be able to predict those older adults who have a severe risk of adrs that may lead to emergency hospital admissions. the development of an adr prediction tool in community settings would facilitate this. the design of such a tool would require identification of a comprehensive list of possible predictive factors contributing […]

library_books

Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models

2014
PMCID: 4178502
PMID: 25278750
DOI: 10.2147/CIA.S65475

[…] adults. standard computerized databases, the gray literature, bibliographies, and citations were searched (2012) to identify relevant peer-reviewed studies. studies that developed and validated an adr prediction model for use in patients over 65 years old, using a multivariable approach in the design and analysis, were included. data were extracted and their quality assessed by independent […]


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adr-prediction institution(s)
Fujitsu Ireland Ltd., Insight Building, IDA Business Park, Lower Dangan, Newcastle, Galway, Ireland
adr-prediction funding source(s)
Supported by the TOMOE project funded by Fujitsu Laboratories Ltd., Japan and Insight Centre for Data Analytics at National University of Ireland Galway (supported by the Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/ 2289).

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The linked repository contains only description of the data, but no code/program