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- 저자 : Chien-Lung Chan (검색결과 4 건)
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Chien-Tai Hong,Lung Chan,Chaur-Jong Hu,Chien-Min Lin,Chien-Yeh Hsu,Ming-Chin Lin 한국유방암학회 2017 Journal of breast cancer Vol.20 No.4
Purpose: Whether tamoxifen affects the risk of neurodegenerative disease is controversial. This nationwide population-based study investigated the risk of Parkinson’s disease (PD) associated with tamoxifen treatment in female patients with breast cancer using Taiwan’s National Health Insurance Research Database. Methods: A total of 5,185 and 5,592 female patients with breast cancer who did and did not, respectively, receive tamoxifen treatment between 2000 and 2009 were included in the study. Patients who subsequently developed PD were identified. A Cox proportional hazards model was used to compare the risk of PD between the aforementioned groups. Results: Tamoxifen did not significantly increase the crude rate of developing PD in female patients with breast cancer (tamoxifen group, 16/5,169; non-tamoxifen group, 11/5,581; p=0.246). Tamoxifen did not significantly increase the adjusted hazard ratio (aHR) for subsequently developing PD (aHR, 1.310; 95% confidence interval [CI], 0.605–2.837; p= 0.494). However, tamoxifen significantly increased the risk of PD among patients followed up for more than 6 years (aHR, 2.435; 95% CI, 1.008–5.882; p=0.048). Conclusion: Tamoxifen treatment may increase the risk of PD in Taiwanese female patients with breast cancer more than 6 years after the initiation of treatment.
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Ting, Hsien-Wei,Chan, Chien-Lung,Pan, Ren-Hao,Lai, Robert K.,Chien, Ting-Ying Korean Institute of Information Scientists and Eng 2017 Journal of Computing Science and Engineering Vol.11 No.4
Spontaneous intracerebral hemorrhage (sICH) has a high mortality rate. Research has demonstrated that sICH occurrence is related to weather conditions; therefore, this study used the decision tree method to explore the impact of climatic risk factors on sICH at different ages. The Taiwan National Health Insurance Research Database (NHIRD) and other open-access data were used in this study. The inclusion criterion was a first-attack sICH. The decision tree algorithm and random forest were implemented in R programming language. We defined a high risk of sICH as more than the average number of cases daily, and the younger, middle-aged and older groups were calculated as having 0.77, 2.26 and 2.60 cases per day, respectively. In total, 22,684 sICH cases were included in this study; 3,102 patients were younger (<44 years, younger group), 9,089 were middle-aged (45-64 years, middle group), and 10,457 were older (>65 years, older group). The risk of sICH in the younger group was not correlated with temperature, wind speed or humidity. The middle group had two decision nodes: a higher risk if the maximum temperature was >$19^{\circ}C$ (probability = 63.7%), and if the maximum temperature was <$19^{\circ}C$ in addition to a wind speed <2.788 (m/s) (probability = 60.9%). The older group had a higher risk if the average temperature was >$23.933^{\circ}C$ (probability = 60.7%). This study demonstrated that the sICH incidence in the younger patients was not significantly correlated with weather factors; that in the middle-aged sICH patients was highly-correlated with the apparent temperature; and that in the older sICH patients was highly-correlated with the mean ambient temperature. "Warm" cold ambient temperatures resulted in a higher risk of sICH, especially in the older patients.
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Hsien-Wei Ting,Chien-Lung Chan,Ren-Hao Pan,Robert K. Lai,Ting-Ying Chien 한국정보과학회 2017 Journal of Computing Science and Engineering Vol.11 No.4
Spontaneous intracerebral hemorrhage (sICH) has a high mortality rate. Research has demonstrated that sICH occurrence is related to weather conditions; therefore, this study used the decision tree method to explore the impact of climatic risk factors on sICH at different ages. The Taiwan National Health Insurance Research Database (NHIRD) and other open-access data were used in this study. The inclusion criterion was a first-attack sICH. The decision tree algorithm and random forest were implemented in R programming language. We defined a high risk of sICH as more than the average number of cases daily, and the younger, middle-aged and older groups were calculated as having 0.77, 2.26 and 2.60 cases per day, respectively. In total, 22,684 sICH cases were included in this study; 3,102 patients were younger (<44 years, younger group), 9,089 were middle-aged (45–64 years, middle group), and 10,457 were older (>65 years, older group). The risk of sICH in the younger group was not correlated with temperature, wind speed or humidity. The middle group had two decision nodes: a higher risk if the maximum temperature was >19°C (probability = 63.7%), and if the maximum temperature was <19°C in addition to a wind speed <2.788 (m/s) (probability = 60.9%). The older group had a higher risk if the average temperature was >23.933°C (probability = 60.7%). This study demonstrated that the sICH incidence in the younger patients was not significantly correlated with weather factors; that in the middle-aged sICH patients was highly-correlated with the apparent temperature; and that in the older sICH patients was highly-correlated with the mean ambient temperature. “Warm” cold ambient temperatures resulted in a higher risk of sICH, especially in the older patients.
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Ching-Yen Kuo,Liang-Chin Yu,Hou-Chaung Chen,Chien-Lung Chan 대한의료정보학회 2018 Healthcare Informatics Research Vol.24 No.1
Objectives: The aims of this study were to compare the performance of machine learning methods for the prediction of themedical costs associated with spinal fusion in terms of profit or loss in Taiwan Diagnosis-Related Groups (Tw-DRGs) andto apply these methods to explore the important factors associated with the medical costs of spinal fusion. Methods: A dataset was obtained from a regional hospital in Taoyuan city in Taiwan, which contained data from 2010 to 2013 on patients ofTw-DRG49702 (posterior and other spinal fusion without complications or comorbidities). Naïve-Bayesian, support vectormachines, logistic regression, C4.5 decision tree, and random forest methods were employed for prediction using WEKA3.8.1. Results: Five hundred thirty-two cases were categorized as belonging to the Tw-DRG49702 group. The mean medicalcost was US $4,549.7, and the mean age of the patients was 62.4 years. The mean length of stay was 9.3 days. The lengthof stay was an important variable in terms of determining medical costs for patients undergoing spinal fusion. The randomforest method had the best predictive performance in comparison to the other methods, achieving an accuracy of 84.30%,a sensitivity of 71.4%, a specificity of 92.2%, and an AUC of 0.904. Conclusions: Our study demonstrated that the randomforest model can be employed to predict the medical costs of Tw-DRG49702, and could inform hospital strategy in terms ofincreasing the financial management efficiency of this operation.
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