논문 및 저서

1. Hwang, H.S., Lee, E.J., Kim, H., Kim, T.W. (2023) "Relationships of Macular Functional Impairment With Structural and Vascular Changes According to Glaucoma Severity", Investigative Ophthalmology and Visual Science, 64(12), DOI:10.1167/iovs.64.12.5

2. Song, J.E., Lee, E.J., Kim, T.W., Kim, H. (2023) "Multicolor imaging compared with red-free fundus photography in the detection of glaucomatous retinal nerve fiber layer thinning", Photodiagnosis and Photodynamic Therapy, 42, DOI:10.1016/j.pdpdt.2023.103352 

3. Lee, J.Y., Park, C.K., Kim, H. (2023) "Real-Time Tunnel Abnormal Sound Detection Algorithm Using Convolutional Neural Networks",한국통신학회논문지, 48(2), 150-161

4. Yoon, J.S., Kim, Y.-E., Lee, E.J., Kim, H., Kim, T.W. (2023) "Systemic factors associated with 10-year glaucoma progression in South Korean population: a single center study based on electronic medical records", Scientific Reports, 13(1), DOI:10.1038/s41598-023-27858-z

5. Lee, E.J., Kim, T.W., Kim, J.A., Lee, S.H., Kim, H., (2022) "Predictive Modeling of Long-Term Glaucoma Progression Based on Initial Ophthalmic Data and Optic Nerve Head Characteristics", Translational Vision Science & Technology, 11(10), DOI:10.1167/tvst.11.10.24 

6. Song, J.S., Lee, Y.B., Kim, J.A., Lee, E.J., Kim, H. (2022) "Association between corneal refractive surgery and the prevalence of glaucoma", British Journal of Ophthalmology, 106(2), 172-176, 2022

7. Kim, A. and Kim, H. (2022) "A new classification tree method with interaction detection capability", Computational Statistics and Data Analysis, 165, DOI: 10.1016/j.csda.2021.107324

8. Kim, J.A., Son, D.H., Lee, E.J, Kim, H., Kim, T.W. (2021) "Intereye Comparison of the Characteristics of the Peripapillary Choroid in Patients with Unilateral Normal-Tension Glaucoma", Ophthalmology Glaucoma, 4(5), 512-521

9. Kim, C.Y., Lee, E.J., Kim, J.A., Kim. H., Kim, T.W. (2021) “Progressive retinal nerve fibre layer thinning and choroidal microvasculature dropout at the location of disc haemorrhage in glaucoma”, British Journal Of Opthalmology, 105(5), 674-680.

10. Han, S. Kim, H. (2021) “Optimal Feature Set Size in Random Forest Regression”, Applied Sciences-Basel, 11(8), 3428.1- 3428.13.

11. Lee, E.J., Kim, J.A., Kim, T.W., Kim, H., Yang, H., Hwang, J.M. (2020), “Glaucoma-like Parapapillary Choroidal Microvasculature Dropout in Patients with Compressive Optic Neuropathy”, Ophthalmology, 127(12), 1652-1662.

12. Han, S., Kim, H., Lee, Y.S. (2020), “Double random forest”, Machine Learning, 109(8), 1569-1586.

13. Kim, J.A., Lee, E.J., Kim, T.W., Kim, H., Girard, M., Mari, J.M., Yang, H., Hwang, J.M. (2020) “Differentiation of Nonarteritic Anterior Ischemic Optic Neuropathy from Normal Tension Glaucoma by Comparison of the Lamina Cribrosa”, Investigative Ophthalmology & Visual Science, Vol 61(8), pp 21.1-21.9.

14. Lee, S., Han, J., Lee, E.J., Kim, T.W., Kim, H., Kim, K. (2020) “Cognitive Impairment and Lamina Cribrosa Thickness in Primary Open-Angle Glaucoma”, Translational Vision Science and Technology, 9(7), 17.1-17.13.

15. Kim, A., Myung, J., Kim, H. (2020) “Random forest ensemble using a weight-adjusted voting algorithm”, Journal of the Korean Data & Information Science Society, 31(2), 427-438.

16. Lee, E.J., Kim, H. (2019) “Effect of Smartphone Use on Intraocular Pressure”, Scientific Reports, 9, 18802.1-18802.7.

17. Lee, E.J., Kim, T.W., Kim, J-A., Kim G-N., Kim, J.M., Girard, M.J.A., Mari, J.M., Kim, H. (2019) “Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma”, Investigative Ophthalmology & Visual Science, Vol 60(10), pp 3343-3351.

18. Kim, G-N., Lee, E.J., Kim, H., Kim, T.W. (2019) “Dynamic Range of the Peripapillary Retinal Vessel Density for Detecting Glaucomatous Visual Field Damage”, Ophthalmology Glaucoma, 2, 103-110.

19. Han, S., and Kim, H. (2019) “On the Optimal Size of Candidate Feature Set in Random forest”, Applied Sciences-Basel, 9, 898.1-898.13

20. Kim, J-A., Lee, E.J., Kim, H., Kim, T.W. (2018) “Steeper structure-function relationship in eyes with than without a parapapillary deep-layer microvasculature dropout”, Scientific Reports, 8, 14182.1-14182.10.

21. Lee, E.J., Kim, T.W., Kim, J-A, Kim, J.A., Kim, H. (2017) “Spontaneous Retinal Venous Pulsation in Unilateral Primary Open-angle Glaucoma With Low Intraocular Pressure”, Journal of Glaucoma, 26, 896-901.

22. Lee, K.M., Lee, E.J., Kim, T.W., Kim, H. (2017) “Pseudophakic Macular Edema in Primary Open-Angle Glaucoma: A Prospective Study Using Spectral-Domain Optical Coherence Tomography”, American Journal of Ophthalmology, 179, 97-109.

23. Gong, J. and Kim, H. (2017) “RHSBoost: Improving classification performance in imbalance data”, Computational Statistics and Data Analysis, 85 1-13.

24. Lee, E.J., Kim, T.W., Lee, K., Lee, S., Kim, H. (2017)“Factors Associated with the Retinal Nerve Fiber Layer Loss after Acute Primary Angle Closure: A Prospective EDI-OCT Study” (with Lee, et al.), PLoS One, 12(1), DOI:10.1371/journal.pone.0168678.

25. Choi, S. and Kim, H. (2016) “Tree size determination for classification ensemble”, Journal of the Korean Data & Information Science Society, 27(1), 255-264.

26. Oh, B.-L., Lee, E.J., Kim, H., Girard, M.J. Mari, J.M., Kim, T.W. (2016) “Anterior Lamina Cribrosa Surface Depth in Open-Angle Glaucoma: Relationship with the Position of the Central Retinal Vessel Trunk”, PLoS One, Vol 11(6), DOI:10.1371/journal.pone.0158443

27. Lee, K.M., Lee, E.J., Kim, T.W., Kim, H. (2016) “Comparison of the Abilities of SD-OCT and SS-OCT in Evaluating the Thickness of the Macular Inner Retinal Layer for Glaucoma Diagnosis”, PLoS One, Vol 11(1), DOI:10.1371/journal.pone.0147964

28. Lee, E.J., Kim, T.W., Lee, D.S., Kim, H., Park, Y.H., Kim, J., Lee J.W., Kim, S. (2016) “Increased CSF tau level is correlated with decreased lamina cribrosa thickness”, Alzheimer's Research & Therapy, Vol 8, DOI:10.1186/s13195-015-0169-3.

29. Lee, E.J., Lee. K.M., Kim, H., Kim, T.W. (2016) “Glaucoma Diagnostic Ability of the New Circumpapillary Retinal Nerve Fiber Layer Thickness Analysis Based on Bruch's Membrane Opening”, Investigative Ophthalmology & Visual Science, Vol 57(10), pp 4194-4204.

30. Suh, M.H., Yoo, B.W., Park, K.H., Kim, J.Y., Kim, H., Kim, H.C. (2015) “Correlation between depth and area of retinal nerve fiber layer defect as measured by spectral domain optical coherence tomography”, Graefe's Archive for Clinical and Experimental Ophthalmology, 253, 925-934.

31. Lee, E.J., Kim, T-W., Kim, M.J., Kim, H. (2015) “Influence of Lamina Cribrosa Thickness and Depth on the Rate of Progressive Retinal Nerve Fiber Layer Thinning”, Ophthalmology, 122(4), 721-729.

32. Suh, M.H., Yoo, B.W., Park, K.H., Kim, H., Kim, H.C. (2015) “Reproducibility of Spectral-domain Optical Coherence Tomography RNFL Map for Glaucomatous and Fellow Normal Eyes in Unilateral Glaucoma”, Journal of Glaucoma, 24(3), 238-244.

33. Chung, D. and Kim, H. (2015) “Accurate Ensemble Pruning with PL-Bagging”. Computational Statistics and Data Analysis, 83, 1-13.

34. Kwak, S. and kim, H. (2014) “Comparison of ensemble pruning methods using Lasso-bagging and WAVE-bagging”, Journal of the Korean Data & Information Science Society, 25(6), 1371-1383.

35. Kim, A., Kim, M., Kim, H. (2014) “Double-Bagging Ensemble Using WAVE”, Communications for Statistical Applications and Methods, 21, 411-422.

36. Kim, Y.W., Lee, E.J., Kim, T.W., Kim, M., Kim, H. (2014)“Microstructure of Beta-Zone Parapapillary Atrophy and the Rate of Retinal-Nerve-Fiber-Layer Thinning in Primary Open-Angle Glaucoma”, Ophthalmology, 121(7), 1341-1349.

37. Chen, Y.-C., Ha, H., Kim, H., Ahn, H. (2014) “Canonical Forest”, Computational Statistics, 29, 849-867.

38. Lee, E.J., Kim, T-W., Weinreb, R.N., Kim, H. (2013)“Reversal of Lamina Cribrosa Displacement Following Intraocular Pressure Reduction in Open Angle Glaucoma Ophthalmology”, Ophthalmology, 120(3), 553-559.

39. Lee, E.J., Kim, T-W., Weinreb, R.N., Suh, M.H., Kim, H. (2013)“Lamina Cribrosa Thickness is not Correlated with Central Corneal Thickness or Axial Length in Healthy Eyes”, Graefe's Archive for Clinical and Experimental Ophthalmology, 251, 847-854.

40. Kim, A.H., Kim, J.H., Kim, H. (2012) “The guideline for choosing the right-size of tree for boosting algorithm”, Journal of the Korean Data & Information Science Society, Vol 23, 949-959.

41. Suh, M.H., Park, K.H., Kim, H., Kim, T.-W., Kim, S.Y., and Kim, D.M. (2012) “Glaucoma Progression after the First-detected Optic Disc Hemorrhage by Optical Coherence Tomography”, Journal of Glaucoma, 21, 358-366.

42. Kim, H. and Guess, F. and Young, T. (2012) “An Extension of Regression Trees to Generate Better Predictive Models”, IIE Transactions, Vol 44, 43-54.

43. Youm, D., Kim, H., Shim, S., Jang, H., Kim, J., Park, K., Choi, C., and Cho, J. (2012) “The Effect of Various Factors on Variability of Retinal Nerve Fiber Layer Thickness Measurements Using Optical Coherence Tomography”, Korean Journal of Ophthalmology, Vol 26, 104-110.

44. Bae, J.H., Han, S.Y., Kim, H., Kim, J.M., Park, K.H., Cho, J.G. (2012) “The effect of axial length on the variability of Stratus optical coherence tomography”, Korean Journal of Ophthalmology, Vol 26, 271-276.

45. Kim, H, Kim, H., Moon, H., and Ahn, H. (2011) “A weight-adjusted voting algorithm for ensembles of classifiers”, Journal of the Korean Statistical Society, Vol 40, 437-449.

46. Kim, D.G., Kim, A., and Kim, H. (2011) “Modified Recursive PCA”, The Korean Journal of Applied Statistics, Vol 24, pp 963-977.

47. Chung, D. and Kim, H. (2011) “Robust Ensemble Methods for Microarray Data”. International Journal of Data Mining and Bioinformatics, Vol 5, 504-518. 

48. Kim, N.R., Kim, C.Y., Kim, H., Seong, G.J., and Lee, E.S. (2011) “Comparison of Goldmann Applanation Tonometer, Noncontact Tonometer, and TonoPen XL for Intraocular Pressure Measurement in Different Types of Glaucomatous, Ocular hypertensive, and Normal Eyes”, Current Eye Research, Vol 36, 295-300.

49. Lee, J., Kim, N.R., Kim, H., Han, J., Lee, E.S., Seong, G.J., and Kim, C.Y. (2011) “Negative refraction power causes underestimation of peripapillary retinal nerve fiber layer thickness in spectral-domain optical coherence tomography tomography”, British Journal Of Opthalmology, Vol 45, 191-202.

50. Kim, J.H., Kim, N.R., Kim, H., Lee, E.S., Seong, G.J., Kim, C.Y. (2011) “Effect of signal strength on reproducibility of circumpapillary retinal nerve fiber layer thickness measurement and its classification by spectral-domain optical coherence tomography”, Japanese Journal Of Ophthalmology, Vol 55, 220-227.

51. Lee, E.S., Kim, H., and Kim, J.M. (2010)“Effect of signal strength on reproducibility of peripapillary retinal nerve fiber layer thickness measurement and its classification by time-domain optical coherence tomography”, Japanese Journal Of Ophthalmology, Vol 54, 414-422.

52. Lee, E.J., Kim, T.W., Park, K.H., Seong, M., Kim, H., Kim, D.M. (2009) “Ability of Stratus OCT to detect progressive retinal nerve fiber layer atrophy in glaucoma”. Investigative Ophthalmology & Visual Science, Vol 50(2), pp 662-668.

53. Kim, H., Kim, W., Moon, J., Kim, A., Im, J., Cho, S. (2008) “Application of Extreme Value Theory for Operational Risk Measurement”. 리스크관리연구, Vol 19, pp 161-182.

54. Kim, H., Kim, W., Lee, S., Im, J., Cho, S., Kim, A. (2008) “A Study on VaR Stability for Operational Risk Management”. The Korean Communications in Statistics, Vol 15, pp 697-708.

55. Choi, W., Lim, J., Lim, J., Kim, H. (2008) “Application of Judgment Post-Stratification to Extended Producer Responsibility System”, The Korean Communications in Statistics, Vol 15, pp 105-115.

56. Kim, H., Loh, W.-Y., Shih, Y.-S., and Chaudhuri, P. (2007)“A Visualizable and Interpretable Regression Model With Good Prediction Power”. IIE Transactions, Vol 39, pp 565-579.

57. Hwang, J.-M., Kim, T.-W., Park, K.-H., Kim, D.-M., Kim, H. (2006) “Correlation Between Topographic Profiles of Localized Retinal Nerve Fiber Layer Defects as Determined by Optical Coherence Tomography and Red-Free Fundus Photography”, Journal of Glaucoma, Vol 15, pp 223-228.

58. Kim, H. (2006) “Bayesian Modeling of Mortality Rates for Colon Cancer”.  The Korean Communications in Statistics, Vol 13, pp 177-190.

59. Kim, H. (2006) “Ordinal Variable Selection in Decision Trees”. The Korean Journal of Applied Statistics, Vol 19, pp 149-161.

60. Ren, S. and Kim, H. (2006) “Use of Modern Statistical Methods in Developing Ecotoxicity QSARs”. in D. Rhodes(eds), New Topics in Environmental Research, Nova Science Publishers, pp 139-153.

61. Kim, H., Nandram, B., Kim, S.-J., Choi, I., Ahn, Y., and Kim, C. (2004) “Marginal Likelihoods for Bayesian Poisson Regression Models”, The Korean Communications in Statistics, Vol 11, pp 381-397.

62. Kim, S.-J., Kim, H. and Lee, K. (2003) “On Tree-based Classifications with Multiresponse Variables”, International Journal of Industrial Engineering, Vol 10, pp 427- 434.

63. Ren, S. and Kim, H. (2003) “Comparative Assessment of Regression Methods for Predicting the Mechanisms of Toxic Action of Phenols”, Journal of Chemical Information and Computer Sciences, Vol 43, pp 2106-2110.

64. Kim, H. and Yates, S. (2003) “Missing Value Algorithms in Decision Trees”, in H. Bozdogan (eds), Statistical Data Mining and Knowledge Discovery, Chapman&Hall/CRC, pp 157-175.

65. Lim, D. and Kim, H. (2003) “Motivation and Learner Characteristics Affecting Online Learning and Learning Application”, Journal of Educational Technology Systems, Vol 31, pp 423-439.

66. Kim, H. and Loh, W.-Y. (2003) “Classification Trees with Bivariate Linear Discriminant Node Models”, Journal of Computational and Graphical Statistics, Vol 12, pp 512-530.

67. Kim, H. (2002) “Combining Decision Trees using Systematic Patterns”, Computing Science and Statistics, Vol 33, 608-617.

68. Nandram, B. and Kim, H. (2002) “Marginal likelihood for a class of Bayesian generalized linear models”, Journal of Statistical Computation and Simulation, Vol 72, pp 319-340.

69. Kim, T., Kim D. M., Park K. H. and Kim, H. (2002) “Neuroprotective Effect of Memantine in a Rabbit Model of Optic Nerve Ischemia”, Korean Journal of Ophthalmology, Vol 16(1), pp 1-7.

70. Kim, H. and Loh, W.-Y. (2001) “Classification Trees with Unbiased Multiway Splits”, Journal of the American Statistical Association, Vol 96, pp 589-604.

71. Kim, H. and Loh, W.-Y. (2001) “2D Classification Trees”, Computing Science and Statistics, Vol 32, pp 294-300.

1. 현대통계학 6판, 김현중 외 3, 다산출판사, 2022

2. 다변량분석입문 2판, 김현중 외 3, KNOU Press, 2022

3. 데이터마이닝 2판, 김현중 외 2, KNOU Press, 2022

4. 실험설계와 분석 10판, 김현중, 자유아카데이, 2021

5. 데이터마이닝, 김현중 외 2, KNOU Press, 2016

6. 실험설계와 분석 8판, 김현중, 자유아카데이, 2015

7. 수리통계학 실제와 응용 8판, 김철응 김현중, 자유아카데미, 2015

8. R 컴퓨팅, 김현중 외 3, KNOU Press, 2014

9. R을 이용한 다변량 분석, 김현중 외 3, KNOU Press, 2014

10. Excel, SPSS, R로 배우는 통계학입문, 김현중 외 7, 자유아카데미, 2012

11. 수리통계학 실제와 응용 7판, 김철응 김현중, 자유아카데미, 2009 

12. 통계학입문, 김현중 외 6, 자유아카데미, 2009.

13. 다변량분석입문, 이용구 김성수 김현중, KNOU Press, 2008.

14. 통계상담, 최병선 김현중 외 공저, 박영사, 1992.

1. Kim, H. (2000 – 2004) 2V Tree, Decision Trees Software System executable on Unix (SUN, DEC), Linux and Windows.

2. Kim, H. and Loh, W.-Y. (1998) “CRUISE: Classification Rule with Unbiased Interaction Selection – User Manual”, Technical Report 989, Department of Statistics, University of Wisconsin – Madison.

3. Kim, H. (1998 – 2011) CRUISE: Classification Rule with Unbiased Interaction Selection, Decision Trees Software System executable on Unix (SUN, DEC), Linux and Windows.

CRUISE 는 제가 개발한 Decision Tree 프로그램입니다. CRUISE는 Classification Rule with Unbiased and Interaction SElection의 약어입니다. CRUISE 프로그램에서 사용된 알고리즘은 저와 University of Wisconsin - Madison, Wei-Yin Loh 교수님과 공동으로 개발하였습니다. 이 알고리즘과 실행파일은 아래의 공식사이트에서 다운로드 받을 수 있습니다. 컴파일된 실행파일은 학문적 목적의 비영리 단체나 개인에게만 무료로 제공됩니다. 영리를 목적으로한 사용은 사전에 저의 허락을 받아야 합니다.

공식 CRUISE 홈페이지