| An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets H Lee, S Yune, M Mansouri, M Kim, SH Tajmir, CE Guerrier, SA Ebert, ... Nature biomedical engineering 3 (3), 173-182, 2019 | 405 | 2019 |
| Deep convolutional neural network–based software improves radiologist detection of malignant lung nodules on chest radiographs Y Sim, MJ Chung, E Kotter, S Yune, M Kim, S Do, K Han, H Kim, S Yang, ... Radiology 294 (1), 199-209, 2020 | 200 | 2020 |
| Machine friendly machine learning: interpretation of computed tomography without image reconstruction H Lee, C Huang, S Yune, SH Tajmir, M Kim, S Do Scientific reports 9 (1), 1-9, 2019 | 47 | 2019 |
| Beyond human perception: sexual dimorphism in hand and wrist radiographs is discernible by a deep learning model S Yune, H Lee, M Kim, SH Tajmir, MS Gee, S Do Journal of Digital Imaging 32, 665-671, 2019 | 36 | 2019 |
| Practical window setting optimization for medical image deep learning H Lee, M Kim, S Do arXiv preprint arXiv:1812.00572, 2018 | 33 | 2018 |
| The fever coach mobile app for participatory influenza surveillance in children: usability study M Kim, S Yune, S Chang, Y Jung, SO Sa, HW Han JMIR mHealth and uHealth 7 (10), e14276, 2019 | 20 | 2019 |
| The Latest Trends in the Useof Deep Learning in Radiology Illustrated Through the Stages of Deep Learning Algorithm Development KD Song, M Kim, S Do Journal of the Korean Society of Radiology 80 (2), 202-212, 2019 | 19 | 2019 |
| Postvaccination fever response rates in children derived using the fever coach mobile app: a retrospective observational study SH Ahn, J Zhiang, H Kim, S Chang, J Shin, M Kim, Y Lee, JH Lee, ... JMIR mHealth and uHealth 7 (4), e12223, 2019 | 11 | 2019 |
| Influenza screening via deep learning using a combination of epidemiological and patient-generated health data: development and validation study H Choo, M Kim, J Choi, J Shin, SY Shin Journal of Medical Internet Research 22 (10), e21369, 2020 | 10 | 2020 |
| Comparative analysis of single and combined antipyretics using patient-generated health data: retrospective observational study YR Park, H Kim, JA Park, SH Ahn, S Chang, JW Shin, M Kim, JH Lee JMIR mHealth and uHealth 9 (5), e21668, 2021 | 5 | 2021 |
| Synho Do, Kyunghwa Han, Hanmyoung Kim, Seungwook Yang, Dong-Jae Lee, and Byoung Wook Choi. Deep convolutional neural network–based software improves radiologist detection of … Y Sim, MJ Chung, E Kotter, S Yune, M Kim Radiology 294 (1), 199-209, 2020 | 5 | 2020 |
| Symptom-Based COVID19 Screening Model Combined with Surveillance Information. D Lee, M Kim, H Choo, SY Shin Studies in Health Technology and Informatics 294, 719-720, 2022 | 1 | 2022 |
| JMIR mHealth and uHealth M Kim, S Yune, S Chang, Y Jung, S Sa, H Han, M Fernandez, G Bron, ... JMIR 2 (4), 2014 | 1 | 2014 |
| Influenza Screening Using Patient-Generated Health Data in Post COVID-19 Pandemic H Choo, M Kim, D Lee, SY Shin Challenges of Trustable AI and Added-Value on Health, 581-582, 2022 | | 2022 |
| Postvaccination Fever Response Rates in Children Derived Using the Fever Coach Mobile App: A Retrospective Observational Study (vol 7, e12223, 2019) SH Ahn, J Zhiang, H Kim, S Chang, J Shin, M Kim, Y Lee, JH Lee, ... JMIR MHEALTH AND UHEALTH 8 (5), 2020 | | 2020 |
| Correction: Postvaccination Fever Response Rates in Children Derived Using the Fever Coach Mobile App: A Retrospective Observational Study SH Ahn, J Zhiang, H Kim, S Chang, J Shin, M Kim, Y Lee, JH Lee, ... JMIR mHealth and uHealth 8 (5), e18921, 2020 | | 2020 |
| 딥러닝 알고리즘 개발과정을 통해 본 영상의학분야에서 딥러닝의 최신 경향 송경두， 김명찬， 도신호 Journal of the Korean Society of Radiology 80 (2), 202-212, 2019 | | 2019 |
| Detecting Influenza Epidemics Using Self-reported Data Through Mobile App (FeverCoach) M Kim, S Yune, HW Han Iproceedings 3 (1), e8686, 2017 | | 2017 |
| Use of Informative Service for Participatory Influenza Surveillance in Children: Fever Coach App M Kim, S Yune, S Chang, Y Jeong, HW Han | | |
