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Keon Woo Park,Young-Hyuc kIm,이지연,Eungho Kim,Hyuk Lee,Bong Geun Song,Joon Oh Park,Kihyun Kim,정철원,Young Suk Park,Won Ki Kang,Mark H. Lee,Keunchil Park 대한암학회 2003 Cancer Research and Treatment Vol.35 No.5
uncommon and typically occurs in patients with disseminated diseases. This may cause difficulty in differentiating it from primary gastric carcinoma. The correct diagnosis of the primary source is important, since the treatment and prognosis of metastatic breast cancer is quite different from those of metastatic gastric cancer. Immunohistochemical staining with GCDFP-15 (gross cystic disease fluid protein-15) can be used to differentiate primary gastric carcinoma and gastric metastasis from breast cancer. We report two cases of gastric metastasis of breast cancer by describing their clinical course, illustrating the histologic findings, and showing the results of immunohistochemical staining with GCDFP-15. (Cancer Res Treat. 2003;35:460-464)
Se-Hoon Lee,Keunchil Park,Cheolwon Suh,Hoon-Kyo Kim,Jun-Suk Kim,Young-Hyuc Kim,Sang-We Kim,Dae-Seog Heo,Yung-Jue Bang,Noe Kyeong Kim 대한암학회 2003 Cancer Research and Treatment Vol.35 No.1
Purpose: A combination of paclitaxel and cisplatin isan effective and safe regimen for advanced non-small celllung cancer (NSCLC). We conducted a multi-center,phase II trial to evaluate the efficacy and safety ofGenexol (paclitaxel) and cisplatin in patients withNSCLC.Materials and Methods: Chemotherapy-naïve patientshaving histologically confirmed NSCLC were enrolled.Genexol was administered at 175 mg/m2 as a 3-hourintravenous infusion and cisplatin at 75 mg/m2 as anintravenous infusion on day 1 every 3 weeks.Results: Twenty-five of 27 patients that were enteredfrom 5 hospitals between Jan 2001 and Aug 2001 receivedchemotherapy. On an intent-to-treat basis, 9 patients(36%) achieved a partial response, 7 patients (28%) astable disease, and 5 patients (20%) progressed. Theoverall response rate was 36% (95% CI, 17 to 55%). Themedian duration of the response was 7.8 months (95%CI, 6.6 to 9.0 months). The median time to progressionwas 7.4 months (95% CI, 5.3 to 9.5 months), and medianoverall survival was 13.3 months (95% CI, 10.8 to 15.9months) for the intent-to-treat population. The major toxicitywas hematological, with grade 3 and 4 neutropeniain 10% (10/106) of the total cycles. The non-hematologictoxicity was mild, and grade 3 emesis was observed in2 patients (8%). One patient experienced a moderatedegree hypersensitivity reaction.Conclusion: The results suggest that a combination ofGenexol and cisplatin is an effective and well-toleratedregimen for patients with NSCLC. (Cancer Res Treat. 2003;35:30-34)
Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning
Kim, Yong-Hyuk,Ha, Ji-Hun,Yoon, Yourim,Kim, Na-Young,Im, Hyo-Hyuc,Sim, Sangjin,Choi, Reno K. Y. Hindawi Publishing Corporation 2016 Computational intelligence and neuroscience Vol.2016 No.-
<P>A correction method using machine learning aims to improve the conventional linear regression (LR) based method for correction of atmospheric pressure data obtained by smartphones. The method proposed in this study conducts clustering and regression analysis with time domain classification. Data obtained in Gyeonggi-do, one of the most populous provinces in South Korea surrounding Seoul with the size of 10,000 km<SUP>2</SUP>, from July 2014 through December 2014, using smartphones were classified with respect to time of day (daytime or nighttime) as well as day of the week (weekday or weekend) and the user's mobility, prior to the expectation-maximization (EM) clustering. Subsequently, the results were analyzed for comparison by applying machine learning methods such as multilayer perceptron (MLP) and support vector regression (SVR). The results showed a mean absolute error (MAE) 26% lower on average when regression analysis was performed through EM clustering compared to that obtained without EM clustering. For machine learning methods, the MAE for SVR was around 31% lower for LR and about 19% lower for MLP. It is concluded that pressure data from smartphones are as good as the ones from national automatic weather station (AWS) network.</P>