• Smart Media Journal
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• v.9 no.4
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• pp.126-133
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• 2020

The treatment policy and prognosis are determined based on the final stage of lung cancer patients. The final stage of lung cancer patients is determined based on the T, N, and M stage classification table provided by the American Cancer Society (AJCC). However, the final stage of AJCC has limitations in its use for various fields such as patient treatment, prognosis and survival days prediction. In this paper, clustering algorithm which is one of non-supervised learning algorithms was assessed in order to check whether using only T, N, M stages with a data science method is effective for classifying the group of patients in the aspect of survival days. The final stage groups and T, N, M stage clustering groups of lung cancer patients were compared by using the cox proportional hazard model. It is confirmed that the accuracy of prediction of survival days with only T, N, M stages becomes higher than the accuracy with the final stages of patients. Especially, the accuracy of prediction of survival days with clustering of T, N, M stages improves when more or less clusters are analyzed than the seven clusters which is same to the number of final stage of AJCC.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.155-164
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• 2022

Objectives : A growing body of evidence links type 2 diabetes (T2D) with a neurodegenerative disease (ND) such as Alzheimer's disease and Parkinson's disease. The purpose of this study is to investigate the relationship between NDs and the development of T2D by comparing the incidence of T2D in a group of various NDs (ND group) and control group. Methods : A population-based 10-year follow-up study was conducted using the Korean National Health Information Database for 2002-2015. We used a retrospective cohort study design to investigate the association of ND with T2D occurrence. The study population included ND (n=8,814) and control (n=37,970) groups, all aged 60 years or over. The Kaplan-Meier method was used to estimate the risk of developing T2D as a function of time. Cox proportional hazards regression models were used to evaluate the relationship between ND and T2D. Results : T2D was developed in a significantly higher percentage of patients in the ND group (53.6%) than in the control group (44.7%). The ND group increased the risk of T2D (HR, 1.43; 95% CI, 1.38-1.47). About one-third of patients in both groups were additionally diagnosed with another ND before the occurrence of T2D during a 10-year follow-up period. When compared to those who did not have another ND during the follow-up period, the incidence of T2D in those who were additionally diagnosed with another ND was higher in both the ND and control groups. Conclusions : The ND group had about 1.4 times higher risk of developing T2D than the control group. Our results showed a positive association between ND and T2D.