140 related articles for article (PubMed ID: 35166342)
21. MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record.
Ahuja Y; Zou Y; Verma A; Buckeridge D; Li Y
J Biomed Inform; 2022 Oct; 134():104190. PubMed ID: 36058522
[TBL] [Abstract][Full Text] [Related]
22. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification.
Beesley LJ; Mukherjee B
Biometrics; 2022 Mar; 78(1):214-226. PubMed ID: 33179768
[TBL] [Abstract][Full Text] [Related]
23. Optimal sampling for positive only electronic health record data.
Lee SH; Ma Y; Wei Y; Chen J
Biometrics; 2023 Dec; 79(4):2974-2986. PubMed ID: 36632649
[TBL] [Abstract][Full Text] [Related]
24. Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes.
Humbert-Droz M; Mukherjee P; Gevaert O
JMIR Med Inform; 2022 Mar; 10(3):e32903. PubMed ID: 35285805
[TBL] [Abstract][Full Text] [Related]
25. Testing calibration of phenotyping models using positive-only electronic health record data.
Zhang L; Ma Y; Herman D; Chen J
Biostatistics; 2022 Jul; 23(3):844-859. PubMed ID: 33616157
[TBL] [Abstract][Full Text] [Related]
26. SAT: a Surrogate-Assisted Two-wave case boosting sampling method, with application to EHR-based association studies.
Liu X; Chubak J; Hubbard RA; Chen Y
J Am Med Inform Assoc; 2022 Apr; 29(5):918-927. PubMed ID: 34962283
[TBL] [Abstract][Full Text] [Related]
27. Robust Semisupervised Deep Generative Model Under Compound Noise.
Chen X
IEEE Trans Neural Netw Learn Syst; 2023 Mar; 34(3):1179-1193. PubMed ID: 34437072
[TBL] [Abstract][Full Text] [Related]
28. Adult patient access to electronic health records.
Ammenwerth E; Neyer S; Hörbst A; Mueller G; Siebert U; Schnell-Inderst P
Cochrane Database Syst Rev; 2021 Feb; 2(2):CD012707. PubMed ID: 33634854
[TBL] [Abstract][Full Text] [Related]
29. The future of Cochrane Neonatal.
Soll RF; Ovelman C; McGuire W
Early Hum Dev; 2020 Nov; 150():105191. PubMed ID: 33036834
[TBL] [Abstract][Full Text] [Related]
30. A Comprehensive and Improved Definition for Hospital-Acquired Pressure Injury Classification Based on Electronic Health Records: Comparative Study.
Sotoodeh M; Zhang W; Simpson RL; Hertzberg VS; Ho JC
JMIR Med Inform; 2023 Feb; 11():e40672. PubMed ID: 36649481
[TBL] [Abstract][Full Text] [Related]
31. Learning from local to global: An efficient distributed algorithm for modeling time-to-event data.
Duan R; Luo C; Schuemie MJ; Tong J; Liang CJ; Chang HH; Boland MR; Bian J; Xu H; Holmes JH; Forrest CB; Morton SC; Berlin JA; Moore JH; Mahoney KB; Chen Y
J Am Med Inform Assoc; 2020 Jul; 27(7):1028-1036. PubMed ID: 32626900
[TBL] [Abstract][Full Text] [Related]
32. Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.
Yuan Q; Cai T; Hong C; Du M; Johnson BE; Lanuti M; Cai T; Christiani DC
JAMA Netw Open; 2021 Jul; 4(7):e2114723. PubMed ID: 34232304
[TBL] [Abstract][Full Text] [Related]
33. Semi-supervised encoding for outlier detection in clinical observation data.
Estiri H; Murphy SN
Comput Methods Programs Biomed; 2019 Nov; 181():104830. PubMed ID: 30658851
[TBL] [Abstract][Full Text] [Related]
34. Informative presence bias in analyses of electronic health records-derived data: a cautionary note.
Harton J; Mitra N; Hubbard RA
J Am Med Inform Assoc; 2022 Jun; 29(7):1191-1199. PubMed ID: 35438796
[TBL] [Abstract][Full Text] [Related]
35. An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records.
Kavuluru R; Rios A; Lu Y
Artif Intell Med; 2015 Oct; 65(2):155-66. PubMed ID: 26054428
[TBL] [Abstract][Full Text] [Related]
36. Collaborative double robust targeted maximum likelihood estimation.
van der Laan MJ; Gruber S
Int J Biostat; 2010 May; 6(1):Article 17. PubMed ID: 20628637
[TBL] [Abstract][Full Text] [Related]
37. Segmented regression with errors in predictors: semi-parametric and parametric methods.
Küchenhoff H; Carroll RJ
Stat Med; 1997 Jan 15-Feb 15; 16(1-3):169-88. PubMed ID: 9004390
[TBL] [Abstract][Full Text] [Related]
38. Bias of Inaccurate Disease Mentions in Electronic Health Record-based Phenotyping.
Kagawa R; Shinohara E; Imai T; Kawazoe Y; Ohe K
Int J Med Inform; 2019 Apr; 124():90-96. PubMed ID: 30784432
[TBL] [Abstract][Full Text] [Related]
39. sureLDA: A multidisease automated phenotyping method for the electronic health record.
Ahuja Y; Zhou D; He Z; Sun J; Castro VM; Gainer V; Murphy SN; Hong C; Cai T
J Am Med Inform Assoc; 2020 Aug; 27(8):1235-1243. PubMed ID: 32548637
[TBL] [Abstract][Full Text] [Related]
40. Writing and reading in the electronic health record: an entirely new world.
Han H; Lopp L
Med Educ Online; 2013 Feb; 18():1-7. PubMed ID: 23394976
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]