Medical illustration
Development of hand gestures recognition using Machine learning for contactless interface system
Paper : Computer Methods and Programs in Biomedicine, Volume 161, July 2018, Pages 39-44
Computer-based dental applications
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Ephidemiology & Complex System
공간 기반 빅데이터 분석: 다양한 환경요인과 질환들 간의 관계 탐색
Altitude and chronic lower respiratory disease mortality
For patients with chronic lower respiratory disease, hypobaric hypoxia at a high altitude is considered a risk factor for mortality. However, the effects of residing at moderately high altitudes remain unclear. We investigated the association between moderate altitude and chronic lower respiratory disease mortality. In particular, we examined the lower 48 United States counties for age-adjusted chronic lower respiratory disease mortality rates, altitude, and socioeconomic factors, including tobacco use, per capita income, population density, sex ratio, unemployment, poverty, and education between 1979 and 1998. The socioeconomic factors were incorporated into the correlation analysis as potential covariates. Considerable positive (R = 0.235; P <0.001) and partial (R = 0.260; P <0.001) correlations were observed between altitude and chronic lower respiratory disease mortality rate. In the subgroup with high COPD prevalence subgroup, even stronger positive (R = 0.346; P <0.001) and partial (R = 0.423, P <0.001) correlations were observed. Multivariate regression analysis of all available socioeconomic factors revealed that additional knowledge on altitude improved the adjusted R2 values from 0.128 to 0.186 for all counties and from 0.301 to 0.421 for counties with high COPD prevalence. We concluded that in the lower 48 United States counties, even a moderate altitude may pose considerable risks in patients with chronic lower respiratory disease.
Economic burden of air pollution (PM10)
Morphometric complexity
Fractal dimension in COPD patients’ lung: spatial distribution of emphysema
The objective of the study was to investigate whether morphometric complexity in the lung can predict survival and act as a new prognostic marker in patients with chronic obstructive pulmonary disease (COPD). COPD (n = 302) patients were retrospectively reviewed. All patients underwent volumetric computed tomography and pulmonary function tests at enrollment (2005–2015). For complexity analysis, we applied power law exponent of the emphysema size distribution (Dsize) as well as box-counting fractal dimension (Dbox3D) analysis. Patients’ survival at February 2017 was ascertained. Univariate and multivariate Cox proportional hazards analyses were performed, and prediction performances of various combinatorial models were compared. Patients were 66 ± 6 years old, had 41 ± 28 pack-years’ smoking history and variable GOLD stages (n = 20, 153, 108 and 21 in stages I−IV). The median follow-up time was 6.1 years (range: 0.2−11.6 years). Sixty-three patients (20.9%) died, of whom 35 died of lung-related causes. In univariate Cox analysis, lower Dsize and Dbox3D were significantly associated with both all-cause and lung-related mortality (both p < 0.001). In multivariate analysis, the backward elimination method demonstrated that Dbox3D, along with age and the BODE index, was an independent predictor of survival (p = 0.014; HR, 2.08; 95%CI, 1.16–3.71). The contributions of Dsize and Dbox3D to the combinatorial survival model were comparable with those of the emphysema index and lung-diffusing capacity. (edited)
