| Year |
Citation |
Score |
| 2024 |
Lee JH, Chae KJ, Park J, Choi SM, Jang MJ, Hwang EJ, Jin GY, Goo JM. Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study. Radiology. Cardiothoracic Imaging. 6: e230287. PMID 38483245 DOI: 10.1148/ryct.230287 |
0.386 |
|
| 2023 |
Lim WH, Lee KH, Lee JH, Park H, Nam JG, Hwang EJ, Chung JH, Goo JM, Park S, Kim YT, Kim H. Diagnostic performance and prognostic value of CT-defined visceral pleural invasion in early-stage lung adenocarcinomas. European Radiology. PMID 37658899 DOI: 10.1007/s00330-023-10204-2 |
0.391 |
|
| 2023 |
Lee JH, Hong H, Nam G, Hwang EJ, Park CM. Effect of Human-AI Interaction on Detection of Malignant Lung Nodules on Chest Radiographs. Radiology. 307: e222976. PMID 37367443 DOI: 10.1148/radiol.222976 |
0.362 |
|
| 2022 |
Lee JH, Hwang EJ, Lim WH, Goo JM. Determination of the optimum definition of growth evaluation for indeterminate pulmonary nodules detected in lung cancer screening. Plos One. 17: e0274583. PMID 36108077 DOI: 10.1371/journal.pone.0274583 |
0.363 |
|
| 2022 |
Lee JH, Hwang EJ, Kim H, Park CM. A narrative review of deep learning applications in lung cancer research: from screening to prognostication. Translational Lung Cancer Research. 11: 1217-1229. PMID 35832457 DOI: 10.21037/tlcr-21-1012 |
0.409 |
|
| 2021 |
Kim Y, Park JY, Hwang EJ, Lee SM, Park CM. Applications of artificial intelligence in the thorax: a narrative review focusing on thoracic radiology. Journal of Thoracic Disease. 13: 6943-6962. PMID 35070379 DOI: 10.21037/jtd-21-1342 |
0.347 |
|
| 2021 |
Hwang EJ, Lee JS, Lee JH, Lim WH, Kim JH, Choi KS, Choi TW, Kim TH, Goo JM, Park CM. Deep Learning for Detection of Pulmonary Metastasis on Chest Radiographs. Radiology. 210578. PMID 34463551 DOI: 10.1148/radiol.2021210578 |
0.339 |
|
| 2021 |
Nam JG, Kim HJ, Lee EH, Hong W, Park J, Hwang EJ, Park CM, Goo JM. Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial. European Radiology. PMID 34264351 DOI: 10.1007/s00330-021-08162-8 |
0.325 |
|
| 2021 |
Hwang EJ, Goo JM, Kim HY, Yi J, Kim Y. Optimum diameter threshold for lung nodules at baseline lung cancer screening with low-dose chest CT: exploration of results from the Korean Lung Cancer Screening Project. European Radiology. PMID 33738597 DOI: 10.1007/s00330-021-07827-8 |
0.461 |
|
| 2020 |
Nam JG, Hwang EJ, Kim DS, Yoo SJ, Choi H, Goo JM, Park CM. Undetected Lung Cancer at Posteroanterior Chest Radiography: Potential Role of a Deep Learning-based Detection Algorithm. Radiology. Cardiothoracic Imaging. 2: e190222. PMID 33778635 DOI: 10.1148/ryct.2020190222 |
0.371 |
|
| 2020 |
Choi H, Qi X, Yoon SH, Park SJ, Lee KH, Kim JY, Lee YK, Ko H, Kim KH, Park CM, Kim YH, Lei J, Hong JH, Kim H, Hwang EJ, et al. Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation. Radiology. Cardiothoracic Imaging. 2: e200107. PMID 33778565 DOI: 10.1148/ryct.2020200107 |
0.306 |
|
| 2020 |
Choi H, Kim H, Hong W, Park J, Hwang EJ, Park CM, Kim YT, Goo JM. Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs. European Radiology. PMID 33125556 DOI: 10.1007/s00330-020-07431-2 |
0.473 |
|
| 2020 |
Hwang EJ, Goo JM, Kim HY, Yoon SH, Jin GY, Yi J, Kim Y. Variability in interpretation of low-dose chest CT using computerized assessment in a nationwide lung cancer screening program: comparison of prospective reading at individual institutions and retrospective central reading. European Radiology. PMID 33123794 DOI: 10.1007/s00330-020-07424-1 |
0.465 |
|
| 2020 |
Lee JH, Sun HY, Park S, Kim H, Hwang EJ, Goo JM, Park CM. Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population. Radiology. 201240. PMID 32960729 DOI: 10.1148/radiol.2020201240 |
0.38 |
|
| 2020 |
Hwang EJ, Goo JM, Kim HY, Yi J, Yoon SH, Kim Y. Implementation of the cloud-based computerized interpretation system in a nationwide lung cancer screening with low-dose CT: comparison with the conventional reading system. European Radiology. PMID 32797309 DOI: 10.1007/s00330-020-07151-7 |
0.482 |
|
| 2020 |
Hwang EJ, Hong JH, Lee KH, Kim JI, Nam JG, Kim DS, Choi H, Yoo SJ, Goo JM, Park CM. Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study. European Radiology. PMID 32162001 DOI: 10.1007/s00330-020-06771-3 |
0.312 |
|
| 2019 |
Suh YJ, Park CM, Han K, Jeon SK, Kim H, Hwang EJ, Lee JH, Paeng JC, Lee CH, Kim YT, Goo JM. Utility of FDG PET/CT for Preoperative Staging of Non-Small Cell Lung Cancers Manifesting as Subsolid Nodules With a Solid Portion of 3 cm or Smaller. Ajr. American Journal of Roentgenology. 1-9. PMID 31846374 DOI: 10.2214/AJR.19.21811 |
0.324 |
|
| 2017 |
Hwang EJ, Goo JM, Kim J, Park SJ, Ahn S, Park CM, Shin YG. Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases. European Radiology. PMID 28050697 DOI: 10.1007/s00330-016-4713-8 |
0.325 |
|
| 2015 |
Lee KH, Goo JM, Lee SM, Park CM, Bahn YE, Kim H, Song YS, Hwang EJ. Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times. Korean Journal of Radiology. 16: 430-9. PMID 25741205 DOI: 10.3348/kjr.2015.16.2.430 |
0.347 |
|
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