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Statistical Inference

1. Duan, R, Cao, M, Ning, Y, Zhu, M, Zhang, B, McDermott, A, Chu, H, Zhou, X, Moore, J, Ibrahim, J, Scharfstein, D, Chen, Y (July, 2019), Global identifiability of latent class models with applications to diagnostic test accuracy studies: a Grobner basis approach, Biometrics (in press).

 

2. Hong, C, Salanti, G, Morton, S, Riley, R, Chu, H, Kimmel, S, Chen, Y, (accepted Sep. 2019) Testing small study effects in multivariate meta-analysis, Biometrics (in press; discussion paper).

 

3. Wang, L, Chai, X, Chen, Y, and Chen, J (2019) Novel Two-Phase Sampling Designs for Studying Binary Outcomes, Biometrics (in press).

4. Duan, R, Cao, M, Ning, Y, Zhu, M, Zhang, B, McDermott, A, Chu, H, Zhou, X, Moore, J, Ibrahim, J, Scharfstein, D, Chen, Y (July, 2019), Global identifiability of latent class models with applications to diagnostic test accuracy studies: a Grobner basis approach, Biometrics (in press).

 

5. Shen, W, Liu, S, Chen, Y and Ning, J. (2018) Regression analysis of longitudinal data with outcome-dependent sampling and informative censoring . Scandinavian Journal of Statistics (Dec. 26, 2018).

 

6. Chen, Y, Huang, J, Ning, Y, Liang, K-Y and Lindsay, B. (2018) A conditional test for composite likelihood with boundary constraints. Biometrika 105 (1), 225-232.

 

7. Huang, J, Ning, Y, Liang, K-Y and Chen, Y. (2018) Composite likelihood inference under boundary conditions, Statistica Sinica, (in press).

 

8. Hong, C, Ning, Y, Wei, P, Cao, Y and Chen, Y. (2017) A semiparametric model for vQTL mapping, Biometrics 73(2): 571-581.

 

9. Hong, C, Ning, Y, Wang, S,Wu, H, Carroll, RJ and Chen, Y. (2017) PLEMT: A novel pseudolikelihood based EM test for homogeneity in generalized exponential tilt mixture models, Journal of the American Statistical Association 112 (50).(This paper won 2015 JSM Biometrics section Byar Awards)

 

10. Chen, Y, Huang, J, Ning, Y, Liang, K-Y and Lindsay, B. (2017) A conditional composite likelihood ratio test with boundary constraints. Biometrika (in press).

 

11. Liu, Y, Chen, Y, and Chu H. (2015) A unification of models for meta-analysis of diagnostic accuracy studies without a gold standard, Biometrics, 71(2):538–47.

 

12. Ning, J, Chen, Y, Cai, C, Huang, X and Wang, MC. (2015) On the Dependence Structure of Bivariate Recurrent Event Processes: Inference and Estimation , Biometrika 102(2): 345-358.

 

13. Chen, Y, Ning, J and Cai, C. (2015) Regression analysis of longitudinal data with irregular and informative observation times, Biostatistics, 16(4): 727-739.

 

14. Ning, Y and Chen, Y. (2015) A class of pseudolikelihood ratio tests for homogeneity in exponential tilt mixture models, Scandinavian Journal of Statistics 42 (2), 504-517.

 

15. Nie, L, Chen, Y, and Chu, H. (2011) Asymptotic Variances of Maximum Likelihood Estimator for the Correlation Coecient from a BVN Distribution with One Variable Subject to Censoring , Journal of Statistical Planning and Inference, 141 (1), 392-401.

 

16. Chen, Y and Liang, KY. (2010) On the asymptotic behaviour of the pseudolike ratio test statistic with boundary problemslihood, Biometrika, 97 (3), 603-620.

 

 

Medical Informatics

17. Huang, J, Chen, Y, Landis, R and Mahoney, K. (2019) Patient portal: how does it change our health behaviors and outcomes? - a retrospective, observational cohort study at Penn Medicine, JMIR (in press). [co-first author]

 

18. Huang, J, Zhang, X, Tong, J, Du, J, Duan, R, Liu, Y, Moore, J, Tao, C and Chen, Y. Comparing drug safety of Hepatitis C therapies using post-market data. BMC Med Inform Decis Mak (2019) 19(Suppl 4): 147. https://doi.org/10.1186/s12911-019-0860-6 (in press).

 

19. Tong, J, Huang, J, Wang, X, Moore, J, Hubbard, R and Chen, Y. (2019) An Augmented Estimation Procedure for EHR-based Association Studies Accounting for Differential Misclassification. Journal of the American Medical Informatics Association (in press).

 

20. Li, R, Duan, R, Kember, R, Regeneron Genetic Center, Rader, D, Damrauer, S, Moore, J and Chen, Y. (2019) A regression framework to uncover pleiotropy in large-scale electronic health record data. Journal of the American Medical Informatics Association, ocz084, https://doi.org/10.1093/jamia/ocz084.

 

21. Du, J, Cunningham, RM, Xiang, Y, Li, F, Jia, Y, Boom, JA, Myneni, S, Bian, J, Luo, C, Chen, Y and Tao, C. (April 2019) Leveraging deep learning to understand health beliefs about the Human Papillomavirus Vaccine from social media. Nature Partner Journal (NPJ) Digital Medicine.

 

22. Li, R, Chen, Y and Moore, J (April 2019). Integration of genetic and clinical information to improve imputation of data missing from electronic health records. Journal of the American Medical Informatics Association.

 

23. Duan, R, Boland, M, Moore, J and Chen, Y (2019). ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. Pacific Symposium on Biocomputing 30-41. [c6].

 

24. Amith, M, Zhu, A, Cunningham, R, Lin, R, Savas, L, Shay, L, Chen, Y, Gong, Y, Boom, J, Roberts, K and Tao, C. (Feb, 2019) Early Usability Assessment of a Conversational Agent for HPV Vaccination, Information Technology and Communications in Health (ITCH) (in press)

 

25. Huang, J, Zhang, X, Du, J, Duan, R, Yang, L, Moore, JH, Chen, Y, Tao, C (Feb 2019), Comparing adverse effects of Hepatitis C drugs using FAERS data, IEEE BIBM 2018 Proceedings.

 

26. Chen, Y, Wang, J, Chubak, J, Hubbard, R (2018) Inflation of type I error rates due to differential misclassification in EHR-derived outcomes: Empirical illustration using breast cancer recurrence, Pharmacoepidemiology & Drug Safety 28(2):264-268

 

27. Moore, J, Olson, RS, Chen, Y, and Sipper, M. (2019) Automated discovery of test statistics using genetic programming, Genetic Programming and Evolvable Machines 20, Issue 1, pp 127–137.

 

28. He, L, Lu, C, Shao, W, Shen, L, Yu, P, Chen, Y and Wang, F. (2018) Multi-Linear Multi-View Clustering, IEEE International Conference on Data Mining (ICDM)

 

29. Hubbard, R, Huang, J, Harton, J, Oganisian, A, Choi, G, Utidjian, L, Eneli, I, Bailey, L, Chen, Y (2018) A Bayesian latent class approach for EHR-based phenotyping, Statistics in Medicine 38:74–87.

 

30. Lin, R, Amith, M, Liang, C, Duan, R, Chen, Y and Tao, C. (July, 2018) Visualized Emotion Ontology: A Model For Representing Visual Cues of Emotions, BMC Medical Informatics and Decision Making 18(Suppl 2): 64

 

 

31. Cao, M, Chen, Y, Fujimoto, K and  Schweinberger, M. (2018) A two-stage working model strategy for network analysis under Hierarchical Exponential Random Graph Models, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (in press).

 

32. Tong, J, Huang, J, Du, J, Cai, Y, Tao, C and Chen, Y. (2018) The Use of Likelihood Ratio Test to Identify Rare Adverse Events with Year-varying Reporting Rates for FLU4 Vaccine in VAERS, AMIA (in press).

 

33. Zhang, X., Duan, R., Du, J., Huang, J., Chen, Y, & Tao, C. (2018). Comparing Pharmacovigilance Outcomes Between FAERS and EMR Data for Acute Mania Patients. 2018 IEEE International Conference on Healthcare Informatics Workshop (ICHI-W) (pp. 57-59). IEEE.

 

34. Duan, R, Zhang, X., Huang, J., Du, J., Tao, C., and Chen, Y. (2018). On the Evidence Consistency of Pharmacovigilance Outcomes between FAERS and EMR Data for Acute Mania Patients. IEEE International Conference on Health Informatics 2018 (in press).

 

35. Huang, J., Du, J., Duan, R., Zhang, X., Tao, C., Chen, Y. (2018) Characterization of the differential adverse event rates by race/ethnicity groups for HPV vaccine by integrating data from different sources. Frontiers in pharmacology 9:539.

 

36. Moore, J, Olson, R, Schmitt, P, Chen, Y and Manduchi, E. (2018) How computational thought experiments can improve our understanding of the genetic architecture of common human diseases, Artificial Life. (in press)

 

37. Huang, J, Duan, R, Hubbard, R,Wu, Y, Moore, JH, Xu, H, and Chen, Y (2017), A prior knowledge guided integrated likelihood estimation method (PIE) for bias reduction in association studies using electronic health records data, Journal of the American Medical Informatics Association (in press).

38. Duan, R, Zhang, X, Du, J, Huang, J, Tao, C, and Chen, Y (2017). Post-marketing Drug Safety Evaluation using Data Mining Based on FAERS. International Conference on Data Mining and Big Data (pp. 379-389). Springer, Cham.

 

39. Huang, J, Zhang, X, Du, J, Duan, R, Yang, L, Moore, JH, Chen, Y, Tao, C (2017), Comparing difference of adverse effects among multiple drugs using FAERSdata, Medinfo (in press).

 

40. Du, J, Huang, J, Duan, R, Chen, Y, Tao, C (2017), Comparing the Human Papillomavirus Vaccination Opinions Trends from Different Twitter User Groups with a Machine Learning Based System and Semiparametric Nonlinear Regression, Medinfo (in press).

 

41. Sun, H, Wang, Y, Chen, Y, Li, Y and Wang, S. (2017) pETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data. Bioinformatics, (in press).

 

42. Cai, Y, Du, J, Huang, J, Ellenberg, S, Hennessy, S, Tao, C, and Chen, Y. (2016) A Signal Detection Method for Temporal Variation of Adverse Effect with Vaccine Adverse Event Reporting System Data. BMC Medical Informatics and Decision Making, (in press).

 

43. Duan, R, Cao, M, Wu, Y, Huang, J, Denny, J, Xu, H and Chen, Y. (2016) An Empirical Study for Impacts of Measurement Errors on EHR based Association Studies, AMIA annual symposium proceedings, 10:1764-1773

(This paper won the first prize of \Best of Student Papers in Knowledge Discovery and Data Mining (KDDM)"Awards)

 

44. Du, J, Cai, Y, Chen, Y and Tao, C. (2016) Trivalent influenza vaccine adverse symptoms analysis based on MedDRA terminology using VAERS data in 2011, Journal of Biomedical Semantics, 7-13.

 

45. Du, J, Cai, Y, Chen, Y, He, Y, and Tao, C. (2016) Analysis of Individual Differences in Vaccine Pharmacovigilance using VAERS Data and MedDRA System Organ Classes: A Use Case Study with Trivalent Influenza Vaccine, Biomedical Informatics Insight, 2016.

 

46. Tao, C, Du, J, Cai, Y and Chen, Y. (2015) Trivalent Influenza Vaccine Adverse Event Analysis Based On MedDRA System Organ Classes Using VAERS Data, Studies in health technology and informatics, 2015. 216:1076.

 

47. Du, J, Cai Y, Chen, Y, Tao C. Adverse Event Analysis for Trivalent In Vaccine Based On MedDRA Terminology Using VAERS Data, International Workshop on Vaccine and Drug Ontology Studies (VDOS)-in conjunction with the International Conference on Biomedical Ontology (ICBO) 2015, Lisbon, July 2015.

 

48. Cao M, Chen, Y, Zhu M, Zhang J. (2015) Automated Evaluation of Medical Software Usage: Algorithm and Statistical Analyses, Studies in health technology and informatics, 2015. 216:965.

 

49. Huang, J, Chen, Y, Swartz, M and Ionita-Laza, I (2014) Family-Based Association Test for Sequence Data with Applications in the GAW 18 Simulated data, BMC Proceedings 8 (Suppl 1): S27, 2014.

 

50. Chen, Y, Ning, Y, Hong, C and Wang, S. (2013) Semiparametric tests for identifying differentially methylated loci with case-control designs using Illumina arrays, Genetic Epidemiology, 38 (1), 42{50.

 

51. Tong P, Chen, Y, Su X and Coombes K (2013) SIBER: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data. Bioinformatics, 29 (5), 605-613.

Comparative Effectiveness Research

52. Singh, J, Kallan, M, Chen, Y, Parks, M, Ibrahim, S. (accepted in Aug, 2019) Race and discharge disposition after Elective Total Knee Arthroplasty: A risk-adjusted analysis of a large database, JAMA Network Open (in press).

 

53. Cai, Y, Huang, J, Ning, J, Lee, ML, Rosner, B and Chen, Y (accepted in July 2019), Two-sample test for correlated data under outcome-dependent sampling with an application to self-reported weight loss data, Statistics in Medicine (in press).

 

54. Wang, L, Rouse, B, Marks-Anglin, A, Duan, R, Shi, Q, Quach, K, Chen, Y, Schmid, CH, Li, T. (June, 2019) Rapid network meta-analysis using trial data from the U.S. Food and Drug Administration approval packages and ClinicalTrials.gov – a case study on first-line medications for open-angle glaucoma. Journal of Clinical Epidemiology (114 (2019) 84-94).

 

55. Lake, E, Jordan, J, Duan, R, and Chen, Y (May 2019) A Meta-Analysis of the Associations between the Nurse Work Environment in Hospitals and Five Sets of Outcomes, Medical Care 59(5) 353-360

 

56. Chiasakul, T, Jesus, E, Tong, J, Chen, Y, Crowther, M, Garcia, D, Chai-Adisaksopha, C, Messe, S and Cuker A. (Nov. 2018) Inherited Thrombophilia and The Risk of Arterial Ischemic Stroke: A Systematic Review and Meta-Analysis, American Society of Hematology Annual meetings 132 no. Suppl 1-2518

 

57. Piao, J, Liu, YL, Chen, Y and Ning, J. (2018) Maximum likelihood estimation and EM algorithm of copas selection model for publication bias correction of diagnostic tests, Statistical Methods in Medical Research (in press).

 

58. Lin, L, Chu, H, Murad, M, Hong, C, Qu, Z, Cole, S, and Chen, Y, Comparison of publication bias tests in Empirical meta-analysis, Journal of General Internal Medicine (in press).

 

59. Zhang, J, Ko, CW, Nie, L, Chen, Y and Tiwari, R (2018) Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies, Statistical Methods in Medical Research, (in press).

 

60. Hong, C, Riley, R and Chen, Y (2017) Robust variance estimator for Riley method of the multivariate meta-analysis when within-study correlations are unknown, Research Synthesis Methods, (in press).

 

61. Agarwal, R, Bartsch, SM, Kelly, BJ, Prewitt, M, Liu, YL, Chen, Y, and Umscheid, CA. (2017) Newer glycopeptide antibiotics for treatment of complicated skin and soft tissue infections: a systematic review, network meta-analysis, and cost analysis, Clinical Microbiology and Infection, (in press).

 

62. Huang, J, Liu, YL, Vitale, S, Penning, T, Whitehead, A, Vachani, A, Clapper, M, Muscat, J, Lazarus, P, Scheet, P, Moore, JH and Chen, Y (2017), On meta- and mega-analyses for gene-environment interactions, Genetic Epidemiology (in press).

 

63. Huang, J, Huang, J, Chen, Y and Ying, G (2017), Evaluation of Approaches to Analyzing Continuous Correlated Eye Data When Sample Size Is Small, Ophthalmic Epidemiology (in press).

 

64. Ma, X, Lian, X, Chu, H, Ibrahim, J, and Chen, Y (2017) A Bayesian hierarchical model for network meta-analysis of diagnostic tests, Biostatistics, (in press)

 

65. Wang, L, Chen, Y and Zhu, H (2017) Implementing Optimal Allocation in Clinical Trials with Multiple Endpoints, Journal of Statistical Planning and Inference 182, 88-99.

 

66. Ning, J, Chen, Y and Piao, J (2017) Maximum likelihood estimation and EM algorithm of Copas selection model for publication bias correction. Biostatistics, (in press).

 

67. Liu, Y, DeSantis, S and Chen, Y (2017) Bayesian mixed treatment comparisons meta-analysis for correlated outcomes subject to reporting bias, Journal of the Royal Statistical Society: Series C, (in press).

 

68. Liu, Y, Chen, Y and Scheet, P (2016), A meta-analytic framework for detection of genetic interactions, Genetic Epidemiology, 40 (7), 534-543.

 

69. Li, X, Chen, Y, and Li, R (2016) A frailty model for recurrent events during alternating restraint and non-restraint time periods, Statistics in Medicine, 20 February 2017.

 

70. Chen, Y, Liu, Y, Chu, H, Lee, M and Schmid, C (2017) A simple and robust method for multivariate meta-analysis of diagnostic test accuracy, Statistics in Medicine, 36(1):105-121.

 

71. Chen, Y, Hong, C, Ning, Y and Su, X. (2016) Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach, Statistics in Medicine, (in press).

 

72. Chahoud, J, Semaan, A, Chen, Y, Cao, M, Rieber, A, Rady, P and Tyring, S. (2016) The Association between Beta-genus Human Papillomavirus and Cutaneous Squamous Cell Carcinoma in Immunocompetent Individuals: a Meta-analysis, JAMA Dermatology, 152(12):1354-1364.

 

73. Chen, Y, Cai, Y, Hong, C, and Jackson, D. (2016) Inference for correlated effect sizes using multiple univariate meta-analyses, Statistics in Medicine, 35(9): 1405-1422.

 

74. Chen, Y, Hong, C and Riley, R. (2015) An alternative pseudolikelihood method for multivariate random-effects meta-analysis, Statistics in Medicine 34 (3): 361-380.

 

75. Chen, Y, Liu, Y, Ning, J, Cormier J and Chu H. (2015) A model for combining case-control and cohort studies in systematic reviews of diagnostic tests, Journal of the Royal Statistical Society: Series C, 64(3): 469-489.

 

76. Chen, Y, Liu, Y, Ning, J, Nie, L, Zhu, H and Chu H. (2014) A composite likelihood method for bivariate analysis of sensitivity and specificity in diagnostic reviews, Statistical Methods in Medical Research.

 

77. Chen, Y, Chu, H, Luo, S, Nie L and Chen S. (2014) Bayesian analysis on meta-nalysis of case-control studies accounting for within-study correlation, Statistical Methods in Medical Research.

 

78. Chen, Y, Luo, S, Chu, H, Su, X and Nie, L. (2014) An Empirical Bayes Method for Multivariate Meta-analysis with Application in Clinical Trials, Communications in Statistics-Theory and Methods, 43(16), 3536-3551.

 

79. Ma, X, Chen, Y, Cole, S and Chu, H. (2014) A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: accounting for partial verification bias, Statistical Methods in Medical Research.

 

80. Luo, S, Chen, Y, Su, X and Chu, H. (2014) mmeta: An R package for multivariate meta-analysis. Journal of Statistical Software, 56 (11).

 

81. Chen, Y, Luo, S, Chu, H and Wei, P. (2013) Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials, Statistics in Biopharmaceutical Research, 5 (2): 142-155.

 

82. Nie, L, Soon, G, Qi, K, Chen, Y and Chu, HT. (2013) A note on partial covariate-adjustment and design considerations in noninferiority trials when patient-level data are not available, Journal of Biopharmaceutical Statistics, 23 (5), 1042-1053.

 

83. Chu, H, Nie, L, Chen, Y, Huang, Y and Sun, W. (2012) Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: methods for the absolute risk difference and relative risk, Statistical Methods in Medical Research, 21 (6): 621-633.

 

Collaborative Papers

84. Ashana, D, Umscheid, C, Stephens-Shields, A, Kohn, R, Madden, V, Harhay, M, Chen, Y, Kerlin, M. (2019) Determining the association between end-of-life care resources and patient outcomes in Pennsylvania intensive care units, Critical Care Medicine.

 

85. Chen, X, Fan, R, Peng, F, Liu, J, Huang, J, Liang, J, Chen, Z, Chen, Y and Jiang, Y. (2019) Blood pressure and body fat percent in women with neuromyelitis optica spectrum disorder and multiple sclerosis, European Journal of Neurology.

 

86. Liu, L, Liang, J, Liu, Q, Luo, C, Liu, J, Fan, R, Chen, Z, Chen, Y, Peng, F, Jiang, Y. (2019) Elevated plasma homocysteine levels in anti-N-methyl-D-aspartate receptor encephalitis. Frontiers in Neurology.

 

87. Gluck, C, Qiu, C, Han, S, Palmer, M, Park, J, Ko, Y, Hanson, R, Huang, J, Chen, Y, Park, A, Mantzaris, I, Verma, A, Li, H, and Susztak, K. (June 2019) Kidney cytosine methylation changes can improve renal function decline estimation in patients with diabetic kidney disease, Nature Communications 10, Article number: 2461 (2019)

 

88. Umscheid, C, Jonathan, W, Matthew, G, Jenna G, Tessa, C, Liu, YL, Chen, Y, and Jennifer, M. (June 2019) National Survey of Hospitalists Experiences with Incidental Pulmonary Nodules. Journal of Hospital Medicine 14(6):353-356

 

89. Leas, B, Kahwati, L, Liu, Y, Chen, Y, D'Anci, K, and Umscheid, C, (2018) Using Qualitative Comparative Analysis (QCA) to Assess Interventions for Improving Asthma Care, Academy Health Research Meeting.

 

90. Jiang, Y, Weng, R, Zhang, Y, Fan, R, Liu, Y, Chen, Z, Peng, F, Chen, Y, and Chen, X, (2018) The performance of rapid plasma reagin (RPR) titer in HIV-negative general paresis after neurosyphilis therapy, BMC Infectious Diseases (in press)

 

91. Qiu, C, Hanson, R, Fufaa, G, Kobes, S, Gluck, C, Huang, J, Chen, Y, Nelson, R, Knowler, W, Susztak, K, (2018) Cytosine methylation changes and prediction of Renal Function decline in American Indians, Kidney International (in press).

 

92. Lu, G, Changb, J, Liu, Z, Chen, Y, Li, M, and Zhu, J. (2016) Phospholipase C Beta 1: A Candidate Signature Gene for Proneural Subtype High-Grade GliomaMolecular Neurobiology 53:6511-6525.

 

93. Liu, L, Xu, H, Wang, W, Wu, C, Chen, Y, Yang, J, Cen, P, Xu, J, Liu, C, Long, J, Guha, S, Fu, D, Ni, Q, Jatoi, A, Chari, S, McCleary-Wheeler, A, Fernandez-Zapico, M, Li, M, Yu, X, (2015) A Preoperative Serum Signature of CEA+/CA125+/CA19-9  1,000 U/mL Indicates Poor Outcome to Pancreatectomy for Pancreatic Cancer, International Journal of Cancer (9), 2216-2227.

 

94. Xu, C, Wallace, M, Yang, J, Jiang, L, Zhai, Q, Zhang, Y, Hong, C, Chen, YFrank, T, Stauer, J, Asbun, H, Raimondo, M, Woodward, T, Li, Z, Guha, S, Zheng, L and Li, M (2014) ZIP4 is a Novel Diagnostic and Prognostic Marker in Human Pancreatic Cancer: A Systemic Comparison Between EUS-FNA and Surgical Specimens, Current Molecular Medicine, 14, 1-7.

 

95. Lin, Y, Chen, Y, Wang, Yy, Yang, Jy, Zhu, V, Liu, Y, Cui, X, Yan, W, Jiang, T, Hergenroeder, G, Fletcher, S, Levine, J, Kim, D, Tandon, N, Zhu, J and Li, M, (2013) ZIP4 is a novel molecular marker for glioma, Neuro-Oncology, 15 (8), 1008-1016. PMID: 21191590.

 

96. Zhang Y, Yang, J, Cui, X, Chen, Y, Zhu, V, Hagan, J, Wang, H, Yu, X, Hodges, S, Fang, J, Chiao, P, Logsdon, C, Fisher, W, Brunicardi, F, Chen, C, Yao, Q, Fernandez-Zapico, M, and Li, M, (2013), A Novel epigenetic CREB-miR 373 Axis Mediates ZIP4-Induced Pancreatic Cancer Growth, EMBO Molecular Medicine, 5 (9), 1322-1334.

 

97. Lin Y, Zhang G, Zhang J, Gao G, Li M, Chen, Y, Wang J, Li G, Song S, Wang Y and Jiang T, (2013) A panel of four cytokines predicts the prognosis of patients with malignant gliomas, Journal of Neuro-Oncology, 114 (2), 199-208.

 

98. Go, VF, Frangakis, C, Minh, N, Latkin, C, Ha, T, Mo, T, Sripaipan, T, Davis, W, Zelaya, C, Chen, Y, Celentano, D and Quan, V, (2013) Effects of an HIV peer prevention intervention on sexual and injecting risk behaviors among injecting drug 10 users and their risk partners in Thai Nguyen, Vietnam: a randomized controlled trial, Social Science & Medicine, 96 154-164.

 

99. Nestadt, G,Wang, Y, Grados, MA, Riddle, MA, Greenberg, BD, Knowles, JA, Fyer, AJ, McCracken, JT, Rauch, SL, Murphy, DL, Rasmussen, SA, Cullen, B, Piacentini, J, Geller, D, Pauls, D, Bienvenu, OJ, Chen, Y, Liang, KY, Goes, FS, Maher, B, Pulver, AE, Shugart, YY, Valle, D, Samuels, JF and Chang, YC (2011) Homeobox genes in obsessive-compulsive disorder, American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 159 (1), 53-60.

 

100. Blom, RM, Samuels, JF, Grados, MA, Chen, Y, Bienvenu, OJ, Riddle, MA, Liang, KY, Brandt, J and Nestadt, G (2011), Cognitive functioning in compulsive hoarding, Journal of Anxiety Disorders, 25 (8), 1139-1144.

 

101. Frangakis, CE, Geschwind J, Kim, D, Chen, Y, Koteish, A, Hong, K, Liapi, E, Georgiades, CS. (2010). Chemoembolization decreases drop-o risk of hepatocellular carcinoma patients on the liver transplant list, Cardiovascular and interventional radiology, 34 (6), 1254-1261.

 

102. Wible, BC, Rilling, WS, Drescher, P, Hieb, RA, Saeian, K, Frangakis, CE, Chen, Y, Eastwood, D., Kim, HS. (2010). Longitudinal Quality of Life Assessment of Patients with Hepatocellular Carcinoma After Primary Transarterial Chemoembolization, Journal of Vascular and Interventional Radiology, 21(7), 1024-

1030.

 

103. Buijs, M, Vossen, JA, Frangakis, CE, Hong, K, Georgiades, C, Chen, Y, Liapi, E, and Geschwind, JF. (2008). Nonresectable Hepatocellular Carcinoma: Long-term Toxicity in Patients Treated with Transarterial Chemoembolization Single-Center Experience. Radiology, 249, 346-354.

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