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Items: 1 to 20 of 272

1.

Automatic generation of case-detection algorithms to identify children with asthma from large electronic health record databases.

Afzal Z, Engelkes M, Verhamme KM, Janssens HM, Sturkenboom MC, Kors JA, Schuemie MJ.

Pharmacoepidemiol Drug Saf. 2013 Aug;22(8):826-33. doi: 10.1002/pds.3438. Epub 2013 Apr 17.

PMID:
23592573
2.

Automating classification of free-text electronic health records for epidemiological studies.

Schuemie MJ, Sen E, 't Jong GW, van Soest EM, Sturkenboom MC, Kors JA.

Pharmacoepidemiol Drug Saf. 2012 Jun;21(6):651-8. doi: 10.1002/pds.3205. Epub 2012 Jan 24.

PMID:
22271492
3.

Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk.

Valkhoff VE, Coloma PM, Masclee GM, Gini R, Innocenti F, Lapi F, Molokhia M, Mosseveld M, Nielsson MS, Schuemie M, Thiessard F, van der Lei J, Sturkenboom MC, Trifirò G; EU-ADR Consortium.

J Clin Epidemiol. 2014 Aug;67(8):921-31. doi: 10.1016/j.jclinepi.2014.02.020. Epub 2014 May 1.

PMID:
24794575
4.

Use of an automated prescription database to identify individuals with asthma.

Osborne ML, Vollmer WM, Johnson RE, Buist AS.

J Clin Epidemiol. 1995 Nov;48(11):1393-7.

PMID:
7490602
5.

Improving automated case finding for ectopic pregnancy using a classification algorithm.

Scholes D, Yu O, Raebel MA, Trabert B, Holt VL.

Hum Reprod. 2011 Nov;26(11):3163-8. doi: 10.1093/humrep/der299. Epub 2011 Sep 12.

6.

Extracting information from the text of electronic medical records to improve case detection: a systematic review.

Ford E, Carroll JA, Smith HE, Scott D, Cassell JA.

J Am Med Inform Assoc. 2016 Sep;23(5):1007-15. doi: 10.1093/jamia/ocv180. Epub 2016 Feb 5. Review.

7.

Validation of Case Finding Algorithms for Hepatocellular Cancer From Administrative Data and Electronic Health Records Using Natural Language Processing.

Sada Y, Hou J, Richardson P, El-Serag H, Davila J.

Med Care. 2016 Feb;54(2):e9-14. doi: 10.1097/MLR.0b013e3182a30373.

8.

Improving sensitivity of machine learning methods for automated case identification from free-text electronic medical records.

Afzal Z, Schuemie MJ, van Blijderveen JC, Sen EF, Sturkenboom MC, Kors JA.

BMC Med Inform Decis Mak. 2013 Mar 2;13:30. doi: 10.1186/1472-6947-13-30.

9.

Predictive value of a cross-cultural asthma case-detection tool in an elementary school population.

Galant SP, Crawford LJ, Morphew T, Jones CA, Bassin S.

Pediatrics. 2004 Sep;114(3):e307-16.

PMID:
15342891
10.

A novel algorithm for detection of adverse drug reaction signals using a hospital electronic medical record database.

Park MY, Yoon D, Lee K, Kang SY, Park I, Lee SH, Kim W, Kam HJ, Lee YH, Kim JH, Park RW.

Pharmacoepidemiol Drug Saf. 2011 Jun;20(6):598-607. doi: 10.1002/pds.2139.

PMID:
21472818
11.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel.

Walsh KE, Cutrona SL, Foy S, Baker MA, Forrow S, Shoaibi A, Pawloski PA, Conroy M, Fine AM, Nigrovic LE, Selvam N, Selvan MS, Cooper WO, Andrade S.

Pharmacoepidemiol Drug Saf. 2013 Nov;22(11):1205-13. doi: 10.1002/pds.3505. Epub 2013 Sep 5.

12.

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

Li Q, Melton K, Lingren T, Kirkendall ES, Hall E, Zhai H, Ni Y, Kaiser M, Stoutenborough L, Solti I.

J Am Med Inform Assoc. 2014 Sep-Oct;21(5):776-84. doi: 10.1136/amiajnl-2013-001914. Epub 2014 Jan 8.

13.

Identification of metastatic cancer in claims data.

Nordstrom BL, Whyte JL, Stolar M, Mercaldi C, Kallich JD.

Pharmacoepidemiol Drug Saf. 2012 May;21 Suppl 2:21-8. doi: 10.1002/pds.3247.

PMID:
22552976
14.

Herpes zoster and postherpetic neuralgia surveillance using structured electronic data.

Klompas M, Kulldorff M, Vilk Y, Bialek SR, Harpaz R.

Mayo Clin Proc. 2011 Dec;86(12):1146-53. doi: 10.4065/mcp.2011.0305. Epub 2011 Oct 13.

15.

Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records.

Cave AJ, Davey C, Ahmadi E, Drummond N, Fuentes S, Kazemi-Bajestani SM, Sharpe H, Taylor M.

NPJ Prim Care Respir Med. 2016 Nov 24;26:16085. doi: 10.1038/npjpcrm.2016.85.

16.

Population-based drug-related anaphylaxis in children and adolescents captured by South Carolina Emergency Room Hospital Discharge Database (SCERHDD) (2000-2002).

West SL, D'Aloisio AA, Ringel-Kulka T, Waller AE, Clayton Bordley W.

Pharmacoepidemiol Drug Saf. 2007 Dec;16(12):1255-67.

PMID:
17918773
17.

A systematic review of validated methods for identifying lymphoma using administrative data.

Herman RA, Gilchrist B, Link BK, Carnahan R.

Pharmacoepidemiol Drug Saf. 2012 Jan;21 Suppl 1:203-12. doi: 10.1002/pds.2315. Review.

PMID:
22262607
18.

Detection of pelvic inflammatory disease: development of an automated case-finding algorithm using administrative data.

Satterwhite CL, Yu O, Raebel MA, Berman S, Howards PP, Weinstock H, Kleinbaum D, Scholes D.

Infect Dis Obstet Gynecol. 2011;2011:428351. doi: 10.1155/2011/428351. Epub 2011 Nov 14.

19.

Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning.

Wang Z, Shah AD, Tate AR, Denaxas S, Shawe-Taylor J, Hemingway H.

PLoS One. 2012;7(1):e30412. doi: 10.1371/journal.pone.0030412. Epub 2012 Jan 19.

20.

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