1 |
Bae, C. Y., Kang, Y. G., Kim, S., et al. (2008). Development of models for predicting biological age (BA) with physical, biochemical, and hormonal parameters, Archives of Gerontology and Geriatrics, 47, 253-265.
DOI
|
2 |
Choi, J., Jang, J., An, Y., and Park, S. K. (2018). Blood pressure and the risk of death from noncardiovascular diseases: a population-based cohort study of Korean adults, Journal of Preventive Medicine and Public Health, 51, 298-309.
DOI
|
3 |
Durand, D. (1941). Risk Elements in Consumer Installment Financing (Technical Ed), National Bureau of Economic Research, New York.
|
4 |
Evans, M., Roberts, A., Davies, S., and Rees, A. (2004). Medical lipid-regulating therapy, Drugs, 64, 1181-1196.
DOI
|
5 |
Finlay, S. (2012). Credit Scoring, Response Modeling, and Insurance Rating: A Practical Guide to Forecasting Consumer Behavior, Palgrave Macmillan, New York.
|
6 |
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, The Journal of Finance, 23, 589-609.
DOI
|
7 |
Furukawa, T., Inoue, M., Kajiya, F., Inada, H., Takasugi, S., Fukui, S., Takeda, H. and Abe, H. (1975). Assessment of biological age by multiple regression analysis, Journal of Gerontology, 30, 422-434.
DOI
|
8 |
Goggins, W. B., Woo, J., Sham, A., and Ho, S. C. (2005). Frailty index as a measure of biological age in a Chinese population, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 60, 1046-1051.
DOI
|
9 |
Hamer, M. M. (1983). Failure prediction: sensitivity of classification accuracy to alternative statistical methods and variable sets, Journal of Accounting and Public Policy, 2, 289-307.
DOI
|
10 |
Hand, D. J. (2009). Measuring classifier performance: a coherent alternative to the area under the ROC curve, Machine learning, 77, 103-123.
DOI
|
11 |
Hernaez, R., Yeh, H. C., Lazo, M., Chung, H. M., Hamilton, J. P., Koteish, A., Potter, J. J., Brancati, F. L., and Clark, J. M. (2013). Elevated ALT and GGT predict all-cause mortality and hepatocellular carcinoma in Taiwanese male: a case-cohort study, Hepatology international, 7, 1040-1049.
DOI
|
12 |
Hong, C. S. and Park, Y. S. (2005). Efficiency comparison of statistical credit evaluation models, Research Institute of Applied Statistics Sungkyunkwan University, 13, 93-107.
|
13 |
Jeon, W. J. and Seo, Y. W. (2018). Analysis of important indicators of TCB using GBM, Journal of Society for e-Business Studies, 22, 159-173.
DOI
|
14 |
Huang, Z., Chen, H., Hsu, C. J., Chen, W. H., and Wu, S. (2004). Credit rating analysis with support vector machines and neural networks: a market comparative study, Decision Support Systems, 37, 543-558.
DOI
|
15 |
Irie, F., Iso, H., Sairenchi, T., et al. (2006). The relationships of proteinuria, serum creatinine, glomerular filtration rate with cardiovascular disease mortality in Japanese general population, Kidney International, 69, 1264-1271.
DOI
|
16 |
Jeon, H. G., Won, J. Y., Peng, X., and Lee, K. C. (2019). Investigating effects of emotional states on the glucose control of diabetes in Korean adults, Journal of Digital Convergence, 17, 301-311.
DOI
|
17 |
Kang, Y. G., Suh, E., Lee, J. W., Kim, D. W., Cho, K. H., and Bae, C. Y. (2018). Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service - Health Screening 11-year follow-up study, Clinical Interventions in Aging, 13, 429-436.
DOI
|
18 |
Katzmarzyk, P. T., Reeder, B. A., Elliott, S., Joffres, M. R., Pahwa, P., Raine, K. D., Kirkland S. A., and Paradis, G. (2012). Body mass index and risk of cardiovascular disease, cancer and all-cause mortality, Canadian Journal of Public Health, 103, 147-151.
DOI
|
19 |
Kim, J. Y., Jang, W. J., and Gim, G. Y. (2019). Development of a personal credit scoring model (COMMERCE Score) using on-line commerce data, Journal of Information Technology and Architecture, 16, 45-55.
DOI
|
20 |
Klemera, P. and Doubal, S. (2006). A new approach to the concept and computation of biological age, Mechanisms of Ageing and Development, 127, 240-248.
DOI
|
21 |
Park, C. S. and Kim, M. S. (2011). Credit evaluation model for medical venture business by the analytic hierarchy process, Asia-Pacific Journal of Business Venturing and Entrepreneurship, 6, 133-147.
|
22 |
Lee, J. Y., Kim, K. H., and Lee, J. S. (2013). Construction of Sample Database from National Health Information Database. Seminar on Application of National Health Information Bigdata.
|
23 |
Martin, M. J., Browner, W. S., Hulley, S. B., Kuller, L. H., and Wentworth, D. (1986). Serum cholesterol, blood pressure, and mortality: implications from a cohort of 361,662 men, The Lancet, 2(8513), 933-936.
|
24 |
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy, Journal of Accounting Research, 18, 109-131.
DOI
|
25 |
Park, J., Cho, B., Kwon, H., and Lee, C. (2009). Developing a biological age assessment equation using principal component analysis and clinical biomarkers of aging in Korean men, Archives of Gerontology and Geriatrics, 49, 7-12.
DOI
|
26 |
Pierleoni, P., Belli, A., Concetti, R., Palma, L., Pinti, F., Raggiunto, S., Sabbatini, L., Valenti, S., and Monteriu, A. (2019). Biological age estimation using an eHealth system based on wearable sensors, Journal of Ambient Intelligence and Humanized Computing, 1-12.
|
27 |
Stocks, T., Van Hemelrijck, M. V., Manjer, J., et al. (2012). Blood pressure and risk of cancer incidence and mortality in the Metabolic Syndrome and Cancer Project, Hypertension, 59, 802-810.
DOI
|
28 |
Wilson, P. W., Abbott, R. D., and Castelli, W. P. (1988). High density lipoprotein cholesterol and mortality. The Framingham Heart Study, Arteriosclerosis, 8, 737-741.
DOI
|
29 |
Yi, S. W., Park, S., Lee, Y. H., Park, H. J., Balkau, B., and Yi, J. J. (2017). Association between fasting glucose and all-cause mortality according to sex and age: a prospective cohort study, Scientific Reports, 7, 1-9.
DOI
|
30 |
Woo, H. S., Lee, S. H., and Cho, H. J. (2013). Building credit scoring models with various types of target variables, Journal of the Korean Data and Information Science Society, 24, 85-94.
DOI
|
31 |
Yoo, J., Kim, Y., Cho, E. R., and Jee, S. H. (2017). Biological age as a useful index to predict seventeen-year survival and mortality in Koreans, BMC Geriatrics, 17, 7.
DOI
|