Literature DB >> 12189274

Application of data mining for examining polypharmacy and adverse effects in cardiology patients.

P Cerrito1.   

Abstract

This article comments upon the use of data mining tools to examine clinical data. Many cardiovascular patients have co-morbid diseases that put them at risk for polypharmacy, or severe adverse reactions from the interactions of multiple medications. Clinical trials typically use too few patients with stringent inclusion/exclusion criteria that prevent an examination of the issue of polypharmacy. However, clinical data collected in the course of patient treatment can be used in conjunction with data mining to find meaningful results.

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Year:  2001        PMID: 12189274     DOI: 10.1385/ct:1:3:177

Source DB:  PubMed          Journal:  Cardiovasc Toxicol        ISSN: 1530-7905            Impact factor:   3.231


  3 in total

Review 1.  Application of data mining techniques in pharmacovigilance.

Authors:  Andrew M Wilson; Lehana Thabane; Anne Holbrook
Journal:  Br J Clin Pharmacol       Date:  2004-02       Impact factor: 4.335

Review 2.  Using text-mining techniques in electronic patient records to identify ADRs from medicine use.

Authors:  Pernille Warrer; Ebba Holme Hansen; Lars Juhl-Jensen; Lise Aagaard
Journal:  Br J Clin Pharmacol       Date:  2012-05       Impact factor: 4.335

3.  Paediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven African countries.

Authors:  Dan K Kajungu; Annette Erhart; Ambrose Otau Talisuna; Quique Bassat; Corine Karema; Carolyn Nabasumba; Michael Nambozi; Halidou Tinto; Peter Kremsner; Martin Meremikwu; Umberto D'Alessandro; Niko Speybroeck
Journal:  PLoS One       Date:  2014-05-01       Impact factor: 3.240

  3 in total

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