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Items: 1 to 50 of 263

1.

Comment on "How pharmacoepidemiology networks can manage distributed analyses to improve replicability and transparency and minimize bias".

Schuemie MJ, Madigan D, Ryan PB, Reich C, Suchard MA, Berlin JA, Hripcsak G.

Pharmacoepidemiol Drug Saf. 2019 May 8. doi: 10.1002/pds.4798. [Epub ahead of print] No abstract available.

PMID:
31066478
2.

Heritability and genome-wide association study of benign prostatic hyperplasia (BPH) in the eMERGE network.

Hellwege JN, Stallings S, Torstenson ES, Carroll R, Borthwick KM, Brilliant MH, Crosslin D, Gordon A, Hripcsak G, Jarvik GP, Linneman JG, Devi P, Peissig PL, Sleiman PAM, Hakonarson H, Ritchie MD, Verma SS, Shang N, Denny JC, Roden DM, Velez Edwards DR, Edwards TL.

Sci Rep. 2019 Apr 15;9(1):6077. doi: 10.1038/s41598-019-42427-z.

3.

Low Screening Rates for Diabetes Mellitus Among Family Members of Affected Relatives.

Polubriaginof FCG, Shang N, Hripcsak G, Tatonetti NP, Vawdrey DK.

AMIA Annu Symp Proc. 2018 Dec 5;2018:1471-1477. eCollection 2018.

4.

Temporal biomedical data analytics.

Moskovitch R, Shahar Y, Wang F, Hripcsak G.

J Biomed Inform. 2019 Feb;90:103092. doi: 10.1016/j.jbi.2018.12.006. Epub 2019 Jan 14. No abstract available.

PMID:
30654029
5.

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use.

Grossman LV, Masterson Creber RM, Ancker JS, Ryan B, Polubriaginof F, Qian M, Alarcon I, Restaino S, Bakken S, Hripcsak G, Vawdrey DK.

Appl Clin Inform. 2019 Jan;10(1):40-50. doi: 10.1055/s-0038-1676971. Epub 2019 Jan 16.

PMID:
30650448
6.

Association of Hemoglobin A1c Levels With Use of Sulfonylureas, Dipeptidyl Peptidase 4 Inhibitors, and Thiazolidinediones in Patients With Type 2 Diabetes Treated With Metformin: Analysis From the Observational Health Data Sciences and Informatics Initiative.

Vashisht R, Jung K, Schuler A, Banda JM, Park RW, Jin S, Li L, Dudley JT, Johnson KW, Shervey MM, Xu H, Wu Y, Natrajan K, Hripcsak G, Jin P, Van Zandt M, Reckard A, Reich CG, Weaver J, Schuemie MJ, Ryan PB, Callahan A, Shah NH.

JAMA Netw Open. 2018 Aug 3;1(4):e181755. doi: 10.1001/jamanetworkopen.2018.1755.

7.

Engaging hospitalized patients with personalized health information: a randomized trial of an inpatient portal.

Masterson Creber RM, Grossman LV, Ryan B, Qian M, Polubriaginof FCG, Restaino S, Bakken S, Hripcsak G, Vawdrey DK.

J Am Med Inform Assoc. 2019 Feb 1;26(2):115-123. doi: 10.1093/jamia/ocy146.

PMID:
30534990
8.

Columbia Open Health Data, clinical concept prevalence and co-occurrence from electronic health records.

Ta CN, Dumontier M, Hripcsak G, Tatonetti NP, Weng C.

Sci Data. 2018 Nov 27;5:180273. doi: 10.1038/sdata.2018.273.

9.

A method for harmonization of clinical abbreviation and acronym sense inventories.

Grossman LV, Mitchell EG, Hripcsak G, Weng C, Vawdrey DK.

J Biomed Inform. 2018 Dec;88:62-69. doi: 10.1016/j.jbi.2018.11.004. Epub 2018 Nov 7.

PMID:
30414475
10.

Effect of vocabulary mapping for conditions on phenotype cohorts.

Hripcsak G, Levine ME, Shang N, Ryan PB.

J Am Med Inform Assoc. 2018 Dec 1;25(12):1618-1625. doi: 10.1093/jamia/ocy124.

11.

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.

Albers DJ, Levine ME, Stuart A, Mamykina L, Gluckman B, Hripcsak G.

J Am Med Inform Assoc. 2018 Oct 1;25(10):1392-1401. doi: 10.1093/jamia/ocy106.

12.

Call for papers: Deep phenotyping for Precision Medicine.

Weng C, Shah N, Hripcsak G.

J Biomed Inform. 2018 Nov;87:66-67. doi: 10.1016/j.jbi.2018.09.017. Epub 2018 Sep 29. No abstract available.

PMID:
30278276
13.

Engaging hospital patients in the medication reconciliation process using tablet computers.

Prey JE, Polubriaginof F, Grossman LV, Masterson Creber R, Tsapepas D, Perotte R, Qian M, Restaino S, Bakken S, Hripcsak G, Efird L, Underwood J, Vawdrey DK.

J Am Med Inform Assoc. 2018 Nov 1;25(11):1460-1469. doi: 10.1093/jamia/ocy115.

PMID:
30189000
14.

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

Levine ME, Albers DJ, Hripcsak G.

J Biomed Inform. 2018 Oct;86:149-159. doi: 10.1016/j.jbi.2018.08.014. Epub 2018 Aug 30.

PMID:
30172760
15.

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.

16.

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.

17.

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.

18.

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.

19.

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.

20.

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 CM, 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 Oct 23;138(17):1839-1849. doi: 10.1161/CIRCULATIONAHA.117.031356.

PMID:
29703846
21.

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.

22.

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.

23.

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.

24.

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.

25.

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
26.

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
27.

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
28.

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.

29.

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.

30.

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.

31.

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.

32.

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.

33.

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. 2018 Sep 28;19(5):863-877. doi: 10.1093/bib/bbx010. Review.

34.
35.

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
36.

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.

37.

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.

38.

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.

39.

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
40.

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.

41.

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.

42.

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.

43.

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.

44.
45.

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.

46.

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.

47.

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.

48.

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.

49.

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.

50.

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.

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