Park S - Search Results

1

Differentiation of predominant subtypes of lung adenocarcinoma using a quantitative radiomics approach on CT.

Park S, Lee SM, Noh HN, Hwang HJ, Kim S, Do KH, Seo JB. Park S, et al. Eur Radiol. 2020 Sep;30(9):4883-4892. doi: 10.1007/s00330-020-06805-w. Epub 2020 Apr 16. Eur Radiol. 2020. PMID: 32300970

2

Application of deep learning-based computer-aided detection system: detecting pneumothorax on chest radiograph after biopsy.

Park S, Lee SM, Kim N, Choe J, Cho Y, Do KH, Seo JB. Park S, et al. Eur Radiol. 2019 Oct;29(10):5341-5348. doi: 10.1007/s00330-019-06130-x. Epub 2019 Mar 26. Eur Radiol. 2019. PMID: 30915557

3

CT Evaluation for Clinical Lung Cancer Staging: Do Multiplanar Measurements Better Reflect Pathologic T-Stage than Axial Measurements?

Park S, Lee SM, Choe J, Lee JG, Lee SM, Do KH, Seo JB. Park S, et al. Korean J Radiol. 2019 Jul;20(7):1207-1215. doi: 10.3348/kjr.2018.0824. Korean J Radiol. 2019. PMID: 31270984 Free PMC article.

4

Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer.

Park S, Lee SM, Do KH, Lee JG, Bae W, Park H, Jung KH, Seo JB. Park S, et al. Among authors: park h. Korean J Radiol. 2019 Oct;20(10):1431-1440. doi: 10.3348/kjr.2019.0212. Korean J Radiol. 2019. PMID: 31544368 Free PMC article.

5

Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings.

Park S, Lee SM, Lee KH, Jung KH, Bae W, Choe J, Seo JB. Park S, et al. Eur Radiol. 2020 Mar;30(3):1359-1368. doi: 10.1007/s00330-019-06532-x. Epub 2019 Nov 20. Eur Radiol. 2020. PMID: 31748854

6

Volume Doubling Times of Lung Adenocarcinomas: Correlation with Predominant Histologic Subtypes and Prognosis.

Park S, Lee SM, Kim S, Lee JG, Choi S, Do KH, Seo JB. Park S, et al. Radiology. 2020 Jun;295(3):703-712. doi: 10.1148/radiol.2020191835. Epub 2020 Mar 31. Radiology. 2020. PMID: 32228296

7

CT in the prediction of margin-negative resection in pancreatic cancer following neoadjuvant treatment: a systematic review and meta-analysis.

Park S, Jang JK, Byun JH, Kim JH, Lee SS, Kim HJ, Hong SB, Park SH. Park S, et al. Among authors: park sh. Eur Radiol. 2021 May;31(5):3383-3393. doi: 10.1007/s00330-020-07433-0. Epub 2020 Oct 30. Eur Radiol. 2021. PMID: 33123793

8

Performance of radiomics models for survival prediction in non-small-cell lung cancer: influence of CT slice thickness.

Park S, Lee SM, Kim S, Choi S, Kim W, Do KH, Seo JB. Park S, et al. Eur Radiol. 2021 May;31(5):2856-2865. doi: 10.1007/s00330-020-07423-2. Epub 2020 Oct 30. Eur Radiol. 2021. PMID: 33128185

9

Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

Park S, Park G, Lee SM, Kim W, Park H, Jung K, Seo JB. Park S, et al. Among authors: park h, park g. Eur Radiol. 2021 Aug;31(8):6239-6247. doi: 10.1007/s00330-020-07620-z. Epub 2021 Feb 8. Eur Radiol. 2021. PMID: 33555355

10

Computer-aided Detection of Subsolid Nodules at Chest CT: Improved Performance with Deep Learning-based CT Section Thickness Reduction.

Park S, Lee SM, Kim W, Park H, Jung KH, Do KH, Seo JB. Park S, et al. Among authors: park h. Radiology. 2021 Apr;299(1):211-219. doi: 10.1148/radiol.2021203387. Epub 2021 Feb 9. Radiology. 2021. PMID: 33560190

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