• Journal of Chest Surgery
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• v.35 no.9
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• pp.659-663
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• 2002

The objective of this study was to assess the usefulness of bone scans in routine preoperative examinations of patients with newly diagnosed non-small cell lung carcinoma. Material and Method: We reviewed the medical records of 258 patients who were newly diagnosed with non-small cell lung cancer in our hospital between January 2000 and December 2000. More than half of the patients (132) were deemed to be inoperable due to their advanced stage based on the CT scans. The remaining 126 patients were considered potentially operable. For these patients, clinical evaluation including the presence of bone pain, serum alkaline phosphatase, and calcium levels was used as clinical predictors of bone metastasis. All patients received bone scans. Bone X-rays, MRI or bone biopsy were performed to confirm the presence of bone metastasis. The usefulness of the bone scan was evaluated by comparing its power of predicting bone metastasis to that of the clinical information. Result: In all patients, the positive and negative predictive values of bone scans for the bone metastasis were 44%, and 99%, respectively. Those of the clinical information were 38% , and 94%. However, in potentially operable patients, the negative predictive value of the clinical information was as high as 99%. Conclusion: If newly diagnosed non-small cell lung cancer patients are presented as potentially operable on the basis of CT scan with no clinical evidence of distant metastases, curative resection could be considered without performing routine bone scans because of the low probability of bone metastasis. However, if there are positive clinical findings, further evaluations, including bone scan should be followed as metastasis will be documented in more than 30% of patients.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Annual Conference of KIPS
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• 2007.05a
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• pp.593-596
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• 2007

복합 질환과 관련된 임상데이터에 대한 예측 모델을 회귀분석, 신경망, 또는 MDR과 같은 방법을 이용하여 분석할 경우 데이터의 차원 문제(Dimensionality Problem)가 발생할 수 있다. 엔트로피(Entropy)를 이용한 의사결정규칙 방법은 이러한 데이터의 차원 문제를 줄이고 의사결정규칙의 결과를 바로 해석할 수 있다는 점에서 질환 예측 모델을 만드는데 유용하다. 본 논문에서는 천식과 관련된 임상데이터를 사용하여 예측 모델을 구성하고 결과를 분석한다.

• Journal of Korea Entertainment Industry Association
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• v.4 no.4
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• pp.72-76
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• 2010

Clinical nomogram is a graphical representation of numeric formula, constructed from clinical cases database of followed patients' treatment, which is used for medical predication. For a clinical nomogram to contribute patient care, it is required to accumulate as many as clinical cases and to extract medical prediction knowledge. It needs to be equipped with an effective method to build medical nomogram with high predication accuracy. It is desirable for medical nomogram to be accessible at patient care point. This paper proposes a medical nomogram service system architecture which takes into account the above-mentioned issues. The proposed system architecture includes a web-based database subsystem to maintain and keep track of clinical cases. On the periodic basis, a new clinical nomogram is reconstructed for the updated clinical database. For the convenient use of patient care practice environment, an app-based program is provided which makes prediction based on the most recent clinical nomogram constructed in the service system. The proposed method has been applied to a clinical nomogram service system development for recurrence and survival prediction in bladder cancer patients.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.646-648
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• 2000

본 논문은 악안면 기형 환자의 해부학적 구조를 기반으로 하여 임상적으로 수술 결과 영상을 생성하는 방법을 제시한다. 이 방법은 환자의 평면 방사선 사진으로부터 환자의 경조직과 연조직의 외곽선을 추출하고, 이를 바탕으로 연조직 이동량 예측 함수를 이용함으로써 환자의 해부학적 특성을 고려한 가상 수술을 수행한다. 예측함수는 경조직 특징점 8개의 이동량에 따른 연조직 특징점 10개의 변화량을 함수로 만든 것으로, 100명의 임상 결과를 바탕으로 도출한 것이다. 또한 환자의 평면 방사선 사진과 특징 부위의 외곽선, 그리고 환자의 외형사진을 쉽게 정합하는 인터페이스를 제공함으로써, 환자의 가상 수술 후 결과를 평면 방사선 사진 및 측면사진으로 표현하는 특징이 있다.

• Annual Conference of KIPS
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• 2006.11a
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• pp.365-368
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• 2006

심장의 활동을 기록한 심전도는 심장의 상태에 대한 가치 있는 임상 정보를 제공한다. 지금까지 심전도를 이용한 심장 질환 진단 알고리즘에 대한 많은 연구가 진행되어 왔으나, 심장 질환에 대한 진단 결과의 부 정확성으로 인해 외국의 진단 알고리즘을 사용하고 있다. 이 논문에서는 원시 심전도 데이터로부터 심장 질환 진단의 파라미터인 ST-segment 추출 방법을 제안한다. ST-segment는 관상동맥질환 예측에 활용되므로 데이터마이닝의 분류기법을 적용하여 질환을 예측한다. 또한 연관규칙 마이닝을 통해 환자들의 임상 데이터로부터 심장 질환자들의 임상적 특징을 예측한다.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.13-22
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• 2021

The clinical decision support system uses accumulated medical data to apply an AI model learned by machine learning to patient diagnosis and treatment prediction. However, the existing black box-based AI application does not provide a valid reason for the result predicted by the system, so there is a limitation in that it lacks explanation. To compensate for these problems, this paper proposes a system model that applies XAI that can be explained in the development stage of the clinical decision support system. The proposed model can supplement the limitations of the black box by additionally applying a specific XAI technology that can be explained to the existing AI model. To show the application of the proposed model, we present an example of XAI application using LIME and SHAP. Through testing, it is possible to explain how data affects the prediction results of the model from various perspectives. The proposed model has the advantage of increasing the user's trust by presenting a specific reason to the user. In addition, it is expected that the active use of XAI will overcome the limitations of the existing clinical decision support system and enable better diagnosis and decision support.

• Journal of the Korean GEO-environmental Society
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• v.18 no.12
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• pp.47-57
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• 2017

In this study, a predictive analysis was conducted on sediment disaster hazard area by selecting six research areas (Chuncheon, Seongnam, Sejong, Daejeon, Miryang and Busan) among the urban sediment disaster preliminary focus management area. The models that were used in the analysis were the existing models (SINMAP and TRIGRS) that are commonly used in predicting sediment disasters as well as the program developed through this study (LSMAP). A comparative analysis was carried out on the results as a means to review the applicability of the developed model. The parameters used in the predictions of sediment disaster hazard area were largely classified into topographic, soil, forest physiognomy and rainfall characteristics. A predictive analysis was carried out using each of the models, and it was found that the analysis using SINMAP, compared to LSMAP and TRIGRS, resulted in a prediction of a wider hazard zone. These results are considered to be due to the difference in analysis parameters applied to each model. In addition, a comparison between LSMAP, where the forest physiognomy characteristics were taken into account, and TRIGRS showed that similar tendencies were observed within a range of -0.04~2.72% for the predicted hazard area. This suggests that the forest physiognomy characteristics of mountain areas have diverse impacts on the stability of slopes, and serve as an important parameter in predicting sediment disaster hazard area.

• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.169-182
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• 2022

This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m² of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m², was damaged.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.665-675
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• 2020

Purpose This study aimed to identify independent predictors of favorable outcomes associated with emergent carotid artery stenting (CAS) in patients with acute anterior circulation stroke. Materials and Methods This study included 93 patients with acute stroke who underwent emergent CAS to treat stenoocclusive lesions in the cervical internal carotid artery (ICA) within 6 hours of the onset of the associated symptoms. Data were compared between patients with and without favorable outcomes. The independent predictors of a favorable outcome were determined via logistic regression analysis (modified Rankin Scale 0-2 at 90 days). Results Intracranial tandem occlusion was noted in 81.7% of patients (76/93) among which (76/93), 55 of whom underwent intracranial recanalization therapy. Intracranial reperfusion was successful in 74.2% (69/93) and favorable outcomes were noted in 51.6% of patients (48/93). The mortality rate was 6.5% (6/93). In logistic regression analysis, diffusion-weighted imaging-Alberta Stroke Program Early CT Score [odds ratio (OR), 1.487; 95% confidence interval (CI), 1.018-2.173, p = 0.04], successful reperfusion (OR, 5.199; 95% CI, 1.566-17.265, p = 0.007), and parenchymal hemorrhage (OR, 0.042; 95% CI, 0.003-0.522, p = 0.014) were independently associated with a favorable outcome. Conclusion Baseline infarct size, reperfusion status, and parenchymal hemorrhage were independent predictors of favorable outcomes after emergent CAS to treat stenoocclusive lesions in the cervical ICA in patients with acute anterior circulation stroke.