76 related articles for article (PubMed ID: 23542991)
1. Adverse drug event prevention in neonatal care: a rule-based approach.
Lazou K; Farini M; Koutkias V; Drossou V; Maglaveras N; Bassiliades N
Stud Health Technol Inform; 2013; 186():170-4. PubMed ID: 23542991
[TBL] [Abstract][Full Text] [Related]
2. Towards a standardised representation of a knowledge base for adverse drug event prevention.
Koutkias V; Lazou K; de Clercq P; Maglaveras N
Stud Health Technol Inform; 2011; 166():139-47. PubMed ID: 21685619
[TBL] [Abstract][Full Text] [Related]
3. Knowledge engineering for adverse drug event prevention: on the design and development of a uniform, contextualized and sustainable knowledge-based framework.
Koutkias V; Kilintzis V; Stalidis G; Lazou K; Niès J; Durand-Texte L; McNair P; Beuscart R; Maglaveras N
J Biomed Inform; 2012 Jun; 45(3):495-506. PubMed ID: 22326287
[TBL] [Abstract][Full Text] [Related]
4. PSIP: an overview of the results and clinical implications.
Beuscart R
Stud Health Technol Inform; 2011; 166():3-12. PubMed ID: 21685604
[TBL] [Abstract][Full Text] [Related]
5. Three different cases of exploiting decision support services for adverse drug event prevention.
Bernonille S; Nies J; Pedersen HG; Guillot B; Maazi M; Berg AL; Sarfati JC; Koutkias V
Stud Health Technol Inform; 2011; 166():180-8. PubMed ID: 21685623
[TBL] [Abstract][Full Text] [Related]
6. The PSIP approach to account for human factors in Adverse Drug Events: preliminary field studies.
Riccioli C; Leroy N; Pelayo S
Stud Health Technol Inform; 2009; 148():197-205. PubMed ID: 19745251
[TBL] [Abstract][Full Text] [Related]
7. A knowledge engineering framework towards clinical support for adverse drug event prevention: the PSIP approach.
Koutkias V; Stalidis G; Chouvarda I; Lazou K; Kilintzis V; Maglaveras N
Stud Health Technol Inform; 2009; 148():131-41. PubMed ID: 19745243
[TBL] [Abstract][Full Text] [Related]
8. Effectiveness of a barcode medication administration system in reducing preventable adverse drug events in a neonatal intensive care unit: a prospective cohort study.
Morriss FH; Abramowitz PW; Nelson SP; Milavetz G; Michael SL; Gordon SN; Pendergast JF; Cook EF
J Pediatr; 2009 Mar; 154(3):363-8, 368.e1. PubMed ID: 18823912
[TBL] [Abstract][Full Text] [Related]
9. The neonatal "sepsis work-up": personal reflections on the development of an evidence-based approach toward newborn infections in a managed care organization.
Escobar GJ
Pediatrics; 1999 Jan; 103(1 Suppl E):360-73. PubMed ID: 9917478
[TBL] [Abstract][Full Text] [Related]
10. Data mining to generate adverse drug events detection rules.
Chazard E; Ficheur G; Bernonville S; Luyckx M; Beuscart R
IEEE Trans Inf Technol Biomed; 2011 Nov; 15(6):823-30. PubMed ID: 21859604
[TBL] [Abstract][Full Text] [Related]
11. Development of a computerised alert system, ADEAS, to identify patients at risk for an adverse drug event.
Rommers MK; Zegers MH; De Clercq PA; Bouvy ML; de Meijer PH; Teepe-Twiss IM; Guchelaar HJ
Qual Saf Health Care; 2010 Dec; 19(6):e35. PubMed ID: 21127096
[TBL] [Abstract][Full Text] [Related]
12. Adverse drug events prevention rules: multi-site evaluation of rules from various sources.
Chazard E; Ficheur G; Merlin B; Serrot E; ; Beuscart R
Stud Health Technol Inform; 2009; 148():102-11. PubMed ID: 19745240
[TBL] [Abstract][Full Text] [Related]
13. The ADE scorecards: a tool for adverse drug event detection in electronic health records.
Chazard E; Băceanu A; Ferret L; Ficheur G
Stud Health Technol Inform; 2011; 166():169-79. PubMed ID: 21685622
[TBL] [Abstract][Full Text] [Related]
14. Information contextualization in decision support modules for adverse drug event prevention.
Nies J; Koutkias V; Kilintzis V; Guillot B; Maglaveras N; Pedersen HG; Berg AL; Skjoet P
Stud Health Technol Inform; 2011; 166():95-104. PubMed ID: 21685615
[TBL] [Abstract][Full Text] [Related]
15. A statistics-based approach of contextualization for adverse drug events detection and prevention.
Chazard E; Bernonville S; Ficheur G; Beuscart R
Stud Health Technol Inform; 2012; 180():766-70. PubMed ID: 22874295
[TBL] [Abstract][Full Text] [Related]
16. Adverse drug events: database construction and in silico prediction.
Cheng F; Li W; Wang X; Zhou Y; Wu Z; Shen J; Tang Y
J Chem Inf Model; 2013 Apr; 53(4):744-52. PubMed ID: 23521697
[TBL] [Abstract][Full Text] [Related]
17. [Detecting adverse drug events during the hospital stay].
Berga Culleré C; Gorgas Torner MQ; Altimiras Ruiz J; Tuset Creus M; Besalduch Martín M; Capdevila Sunyer M; Torres Gubert M; Casajoana Cortinas MT; Baró Sabaté E; Fernández Solà JR; Moron i Besolí A; Odena Estradé E; Serrais Benavente J; Vitales Farrero MT; Codina Jané C
Farm Hosp; 2009; 33(6):312-23. PubMed ID: 20038390
[TBL] [Abstract][Full Text] [Related]
18. Outpatient adverse drug events identified by screening electronic health records.
Gandhi TK; Seger AC; Overhage JM; Murray MD; Hope C; Fiskio J; Teal E; Bates DW
J Patient Saf; 2010 Jun; 6(2):91-6. PubMed ID: 22130350
[TBL] [Abstract][Full Text] [Related]
19. Real-time multidimensional temporal analysis of complex high volume physiological data streams in the neonatal intensive care unit.
McGregor C; James A; Eklund M; Sow D; Ebling M; Blount M
Stud Health Technol Inform; 2013; 192():362-6. PubMed ID: 23920577
[TBL] [Abstract][Full Text] [Related]
20. Factorial switching linear dynamical systems applied to physiological condition monitoring.
Quinn JA; Williams CK; McIntosh N
IEEE Trans Pattern Anal Mach Intell; 2009 Sep; 31(9):1537-51. PubMed ID: 19574617
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]