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Items: 1 to 50 of 249

1.

MAO inhibitory activity of bromo-2-phenylbenzofurans: synthesis, in vitro study, and docking calculations.

Delogu GL, Pintus F, Mayán L, Matos MJ, Vilar S, Munín J, Fontenla JA, Hripcsak G, Borges F, Viña D.

Medchemcomm. 2017 Jul 7;8(9):1788-1796. doi: 10.1039/c7md00311k. eCollection 2017 Sep 1.

2.

Improving reproducibility by using high-throughput observational studies with empirical calibration.

Schuemie MJ, Ryan PB, Hripcsak G, Madigan D, Suchard MA.

Philos Trans A Math Phys Eng Sci. 2018 Sep 13;376(2128). pii: 20170356. doi: 10.1098/rsta.2017.0356.

PMID:
30082302
3.

Deep Phenotyping on Electronic Health Records Facilitates Genetic Diagnosis by Clinical Exomes.

Son JH, Xie G, Yuan C, Ena L, Li Z, Goldstein A, Huang L, Wang L, Shen F, Liu H, Mehl K, Groopman EE, Marasa M, Kiryluk K, Gharavi AG, Chung WK, Hripcsak G, Friedman C, Weng C, Wang K.

Am J Hum Genet. 2018 Jul 5;103(1):58-73. doi: 10.1016/j.ajhg.2018.05.010. Epub 2018 Jun 28.

PMID:
29961570
4.

A Data Quality Assessment Guideline for Electronic Health Record Data Reuse.

Weiskopf NG, Bakken S, Hripcsak G, Weng C.

EGEMS (Wash DC). 2017 Sep 4;5(1):14. doi: 10.5334/egems.218.

5.

Disease Heritability Inferred from Familial Relationships Reported in Medical Records.

Polubriaginof FCG, Vanguri R, Quinnies K, Belbin GM, Yahi A, Salmasian H, Lorberbaum T, Nwankwo V, Li L, Shervey MM, Glowe P, Ionita-Laza I, Simmerling M, Hripcsak G, Bakken S, Goldstein D, Kiryluk K, Kenny EE, Dudley J, Vawdrey DK, Tatonetti NP.

Cell. 2018 Jun 14;173(7):1692-1704.e11. doi: 10.1016/j.cell.2018.04.032. Epub 2018 May 17.

PMID:
29779949
6.

LPA Variants are Associated with Residual Cardiovascular Risk in Patients Receiving Statins.

Wei WQ, Li X, Feng Q, Kubo M, Kullo IJ, Peissig PL, Karlson EW, Jarvik GP, Lee MTM, Shang N, Larson EA, Edwards T, Shaffer C, Mosley JD, Maeda S, Horikoshi M, Ritchie M, Williams MS, Larson EB, Crosslin DR, Bland ST, Pacheco JA, Rasmussen-Torvik LJ, Cronkite D, Hripcsak G, Cox NJ, Wilke RA, Stein CM, Rotter JI, Momozawa Y, Roden DM, Krauss RM, Denny JC.

Circulation. 2018 Apr 27. pii: CIRCULATIONAHA.117.031356. doi: 10.1161/CIRCULATIONAHA.117.031356. [Epub ahead of print]

PMID:
29703846
7.

Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data.

Schuemie MJ, Hripcsak G, Ryan PB, Madigan D, Suchard MA.

Proc Natl Acad Sci U S A. 2018 Mar 13;115(11):2571-2577. doi: 10.1073/pnas.1708282114.

8.

Clinical Information Systems Integration in New York City's First Mobile Stroke Unit.

Kummer BR, Lerario MP, Navi BB, Ganzman AC, Ribaudo D, Mir SA, Pishanidar S, Lekic T, Williams O, Kamel H, Marshall RS, Hripcsak G, Elkind MSV, Fink ME.

Appl Clin Inform. 2018 Jan;9(1):89-98. doi: 10.1055/s-0037-1621704. Epub 2018 Feb 7.

PMID:
29415308
9.

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.

Albers DJ, Elhadad N, Claassen J, Perotte R, Goldstein A, Hripcsak G.

J Biomed Inform. 2018 Feb;78:87-101. doi: 10.1016/j.jbi.2018.01.004. Epub 2018 Jan 31.

10.

Beyond discrimination: A comparison of calibration methods and clinical usefulness of predictive models of readmission risk.

Walsh CG, Sharman K, Hripcsak G.

J Biomed Inform. 2017 Dec;76:9-18. doi: 10.1016/j.jbi.2017.10.008. Epub 2017 Oct 24.

PMID:
29079501
11.

High-fidelity phenotyping: richness and freedom from bias.

Hripcsak G, Albers DJ.

J Am Med Inform Assoc. 2017 Oct 12. doi: 10.1093/jamia/ocx110. [Epub ahead of print]

PMID:
29040596
12.

Uncovering exposures responsible for birth season - disease effects: a global study.

Boland MR, Parhi P, Li L, Miotto R, Carroll R, Iqbal U, Nguyen PA, Schuemie M, You SC, Smith D, Mooney S, Ryan P, Li YJ, Park RW, Denny J, Dudley JT, Hripcsak G, Gentine P, Tatonetti NP.

J Am Med Inform Assoc. 2017 Sep 28. doi: 10.1093/jamia/ocx105. [Epub ahead of print]

PMID:
29036387
13.

A conceptual framework for evaluating data suitability for observational studies.

Shang N, Weng C, Hripcsak G.

J Am Med Inform Assoc. 2017 Sep 8. doi: 10.1093/jamia/ocx095. [Epub ahead of print]

PMID:
29024976
14.

Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data.

Mamykina L, Heitkemper EM, Smaldone AM, Kukafka R, Cole-Lewis HJ, Davidson PG, Mynatt ED, Cassells A, Tobin JN, Hripcsak G.

J Biomed Inform. 2017 Dec;76:1-8. doi: 10.1016/j.jbi.2017.09.013. Epub 2017 Sep 30.

15.

Risk of angioedema associated with levetiracetam compared with phenytoin: Findings of the observational health data sciences and informatics research network.

Duke JD, Ryan PB, Suchard MA, Hripcsak G, Jin P, Reich C, Schwalm MS, Khoma Y, Wu Y, Xu H, Shah NH, Banda JM, Schuemie MJ.

Epilepsia. 2017 Aug;58(8):e101-e106. doi: 10.1111/epi.13828. Epub 2017 Jul 6.

16.

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

Nissim N, Shahar Y, Elovici Y, Hripcsak G, Moskovitch R.

Artif Intell Med. 2017 Sep;81:12-32. doi: 10.1016/j.artmed.2017.03.003. Epub 2017 Apr 27.

17.

Personalized glucose forecasting for type 2 diabetes using data assimilation.

Albers DJ, Levine M, Gluckman B, Ginsberg H, Hripcsak G, Mamykina L.

PLoS Comput Biol. 2017 Apr 27;13(4):e1005232. doi: 10.1371/journal.pcbi.1005232. eCollection 2017 Apr.

18.

EHR-based phenotyping: Bulk learning and evaluation.

Chiu PH, Hripcsak G.

J Biomed Inform. 2017 Jun;70:35-51. doi: 10.1016/j.jbi.2017.04.009. Epub 2017 Apr 12.

19.

Detection of drug-drug interactions through data mining studies using clinical sources, scientific literature and social media.

Vilar S, Friedman C, Hripcsak G.

Brief Bioinform. 2017 Feb 17. doi: 10.1093/bib/bbx010. [Epub ahead of print]

PMID:
28334070
20.
21.

New insights into highly potent tyrosinase inhibitors based on 3-heteroarylcoumarins: Anti-melanogenesis and antioxidant activities, and computational molecular modeling studies.

Pintus F, Matos MJ, Vilar S, Hripcsak G, Varela C, Uriarte E, Santana L, Borges F, Medda R, Di Petrillo A, Era B, Fais A.

Bioorg Med Chem. 2017 Mar 1;25(5):1687-1695. doi: 10.1016/j.bmc.2017.01.037. Epub 2017 Jan 31.

PMID:
28189394
22.

Computational Drug Target Screening through Protein Interaction Profiles.

Vilar S, Quezada E, Uriarte E, Costanzi S, Borges F, Viña D, Hripcsak G.

Sci Rep. 2016 Nov 15;6:36969. doi: 10.1038/srep36969.

23.

Pharmacogenetic polymorphism as an independent risk factor for frequent hospitalizations in older adults with polypharmacy: a pilot study.

Finkelstein J, Friedman C, Hripcsak G, Cabrera M.

Pharmgenomics Pers Med. 2016 Oct 14;9:107-116. eCollection 2016.

24.

Robust empirical calibration of p-values using observational data.

Schuemie MJ, Hripcsak G, Ryan PB, Madigan D, Suchard MA.

Stat Med. 2016 Sep 30;35(22):3883-8. doi: 10.1002/sim.6977. No abstract available.

25.

In Reply to Corbridge and to Schattner.

Mamykina L, Vawdrey D, Hripcsak G.

Acad Med. 2016 Sep;91(9):1192. doi: 10.1097/ACM.0000000000001314. No abstract available.

PMID:
27576036
26.

Patient Experiences Using an Inpatient Personal Health Record.

Woollen J, Prey J, Wilcox L, Sackeim A, Restaino S, Raza ST, Bakken S, Feiner S, Hripcsak G, Vawdrey D.

Appl Clin Inform. 2016 Jun 1;7(2):446-60. doi: 10.4338/ACI-2015-10-RA-0130. eCollection 2016.

27.

Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection.

Moskovitch R, Choi H, Hripcsak G, Tatonetti N.

IEEE/ACM Trans Comput Biol Bioinform. 2017 May-Jun;14(3):555-563. doi: 10.1109/TCBB.2016.2591539. Epub 2016 Jul 14.

28.

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

Vilar S, Hripcsak G.

J Cheminform. 2016 Jul 1;8:35. doi: 10.1186/s13321-016-0147-1. eCollection 2016.

29.

Characterizing treatment pathways at scale using the OHDSI network.

Hripcsak G, Ryan PB, Duke JD, Shah NH, Park RW, Huser V, Suchard MA, Schuemie MJ, DeFalco FJ, Perotte A, Banda JM, Reich CG, Schilling LM, Matheny ME, Meeker D, Pratt N, Madigan D.

Proc Natl Acad Sci U S A. 2016 Jul 5;113(27):7329-36. doi: 10.1073/pnas.1510502113. Epub 2016 Jun 6.

30.
31.

Potential utility of precision medicine for older adults with polypharmacy: a case series study.

Finkelstein J, Friedman C, Hripcsak G, Cabrera M.

Pharmgenomics Pers Med. 2016 Apr 15;9:31-45. doi: 10.2147/PGPM.S101474. eCollection 2016.

32.

Revealing structures in narratives: A mixed-methods approach to studying interdisciplinary handoff in critical care.

Mamykina L, Jiang S, Collins SA, Twohig B, Hirsh J, Hripcsak G, Stanley Hum R, Kaufman DR.

J Biomed Inform. 2016 Aug;62:117-24. doi: 10.1016/j.jbi.2016.03.025. Epub 2016 Apr 7.

33.

How Do Residents Spend Their Shift Time? A Time and Motion Study With a Particular Focus on the Use of Computers.

Mamykina L, Vawdrey DK, Hripcsak G.

Acad Med. 2016 Jun;91(6):827-32. doi: 10.1097/ACM.0000000000001148.

34.

Improving condition severity classification with an efficient active learning based framework.

Nissim N, Boland MR, Tatonetti NP, Elovici Y, Hripcsak G, Shahar Y, Moskovitch R.

J Biomed Inform. 2016 Jun;61:44-54. doi: 10.1016/j.jbi.2016.03.016. Epub 2016 Mar 22.

35.

Preserving temporal relations in clinical data while maintaining privacy.

Hripcsak G, Mirhaji P, Low AF, Malin BA.

J Am Med Inform Assoc. 2016 Nov;23(6):1040-1045. doi: 10.1093/jamia/ocw001. Epub 2016 Mar 24.

36.

Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

Ochs C, He Z, Zheng L, Geller J, Perl Y, Hripcsak G, Musen MA.

J Biomed Inform. 2016 Jun;61:63-76. doi: 10.1016/j.jbi.2016.03.007. Epub 2016 Mar 14.

37.

Engaging hospitalized patients in clinical care: Study protocol for a pragmatic randomized controlled trial.

Masterson Creber R, Prey J, Ryan B, Alarcon I, Qian M, Bakken S, Feiner S, Hripcsak G, Polubriaginof F, Restaino S, Schnall R, Strong P, Vawdrey D.

Contemp Clin Trials. 2016 Mar;47:165-71. doi: 10.1016/j.cct.2016.01.005. Epub 2016 Jan 18.

38.

Structured scaffolding for reflection and problem solving in diabetes self-management: qualitative study of mobile diabetes detective.

Mamykina L, Heitkemper EM, Smaldone AM, Kukafka R, Cole-Lewis H, Davidson PG, Mynatt ED, Tobin JN, Cassells A, Goodman C, Hripcsak G.

J Am Med Inform Assoc. 2016 Jan;23(1):129-36. doi: 10.1093/jamia/ocv169. Epub 2016 Jan 14.

39.

Practical considerations in genomic decision support: The eMERGE experience.

Herr TM, Bielinski SJ, Bottinger E, Brautbar A, Brilliant M, Chute CG, Cobb BL, Denny JC, Hakonarson H, Hartzler AL, Hripcsak G, Kannry J, Kohane IS, Kullo IJ, Lin S, Manzi S, Marsolo K, Overby CL, Pathak J, Peissig P, Pulley J, Ralston J, Rasmussen L, Roden DM, Tromp G, Uphoff T, Weng C, Wolf W, Williams MS, Starren J.

J Pathol Inform. 2015 Sep 28;6:50. doi: 10.4103/2153-3539.165999. eCollection 2015.

40.

Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management.

Cole-Lewis HJ, Smaldone AM, Davidson PR, Kukafka R, Tobin JN, Cassells A, Mynatt ED, Hripcsak G, Mamykina L.

Int J Med Inform. 2016 Jan;85(1):96-103. doi: 10.1016/j.ijmedinf.2015.08.003. Epub 2015 Aug 8.

41.

Feasibility of Prioritizing Drug-Drug-Event Associations Found in Electronic Health Records.

Banda JM, Callahan A, Winnenburg R, Strasberg HR, Cami A, Reis BY, Vilar S, Hripcsak G, Dumontier M, Shah NH.

Drug Saf. 2016 Jan;39(1):45-57. doi: 10.1007/s40264-015-0352-2.

42.

Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers.

Hripcsak G, Duke JD, Shah NH, Reich CG, Huser V, Schuemie MJ, Suchard MA, Park RW, Wong IC, Rijnbeek PR, van der Lei J, Pratt N, Norén GN, Li YC, Stang PE, Madigan D, Ryan PB.

Stud Health Technol Inform. 2015;216:574-8.

43.

Origins of the Arden Syntax.

Hripcsak G, Wigertz OB, Clayton PD.

Artif Intell Med. 2015 Jul 2. pii: S0933-3657(15)00064-0. doi: 10.1016/j.artmed.2015.05.006. [Epub ahead of print]

PMID:
26254699
44.

Improving Detection of Arrhythmia Drug-Drug Interactions in Pharmacovigilance Data through the Implementation of Similarity-Based Modeling.

Vilar S, Lorberbaum T, Hripcsak G, Tatonetti NP.

PLoS One. 2015 Jun 12;10(6):e0129974. doi: 10.1371/journal.pone.0129974. eCollection 2015.

45.

Development of novel adenosine receptor ligands based on the 3-amidocoumarin scaffold.

Matos MJ, Vilar S, Kachler S, Celeiro M, Vazquez-Rodriguez S, Santana L, Uriarte E, Hripcsak G, Borges F, Klotz KN.

Bioorg Chem. 2015 Aug;61:1-6. doi: 10.1016/j.bioorg.2015.05.008. Epub 2015 May 22.

PMID:
26042529
46.

Birth month affects lifetime disease risk: a phenome-wide method.

Boland MR, Shahn Z, Madigan D, Hripcsak G, Tatonetti NP.

J Am Med Inform Assoc. 2015 Sep;22(5):1042-53. doi: 10.1093/jamia/ocv046. Epub 2015 Jun 2.

47.

Informatics to support the IOM social and behavioral domains and measures.

Hripcsak G, Forrest CB, Brennan PF, Stead WW.

J Am Med Inform Assoc. 2015 Jul;22(4):921-4. doi: 10.1093/jamia/ocv035. Epub 2015 Apr 24.

48.

Development and validation of a classification approach for extracting severity automatically from electronic health records.

Boland MR, Tatonetti NP, Hripcsak G.

J Biomed Semantics. 2015 Apr 6;6:14. doi: 10.1186/s13326-015-0010-8. eCollection 2015.

49.

3D pharmacophoric similarity improves multi adverse drug event identification in pharmacovigilance.

Vilar S, Tatonetti NP, Hripcsak G.

Sci Rep. 2015 Mar 6;5:8809. doi: 10.1038/srep08809.

50.

Parameterizing time in electronic health record studies.

Hripcsak G, Albers DJ, Perotte A.

J Am Med Inform Assoc. 2015 Jul;22(4):794-804. doi: 10.1093/jamia/ocu051. Epub 2015 Feb 26.

PMID:
25725004

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