Cargando…
An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research
Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping r...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628158/ https://www.ncbi.nlm.nih.gov/pubmed/34719891 http://dx.doi.org/10.3348/kjr.2021.0170 |
_version_ | 1784606963424821248 |
---|---|
author | Kim, Sungchul Cho, Sungman Cho, Kyungjin Seo, Jiyeon Nam, Yujin Park, Jooyoung Kim, Kyuri Kim, Daeun Hwang, Jeongeun Yun, Jihye Jang, Miso Lee, Hyunna Kim, Namkug |
author_facet | Kim, Sungchul Cho, Sungman Cho, Kyungjin Seo, Jiyeon Nam, Yujin Park, Jooyoung Kim, Kyuri Kim, Daeun Hwang, Jeongeun Yun, Jihye Jang, Miso Lee, Hyunna Kim, Namkug |
author_sort | Kim, Sungchul |
collection | PubMed |
description | Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet. |
format | Online Article Text |
id | pubmed-8628158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Korean Society of Radiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-86281582021-12-07 An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research Kim, Sungchul Cho, Sungman Cho, Kyungjin Seo, Jiyeon Nam, Yujin Park, Jooyoung Kim, Kyuri Kim, Daeun Hwang, Jeongeun Yun, Jihye Jang, Miso Lee, Hyunna Kim, Namkug Korean J Radiol Technology, Experiment, and Physics Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet. The Korean Society of Radiology 2021-12 2021-10-26 /pmc/articles/PMC8628158/ /pubmed/34719891 http://dx.doi.org/10.3348/kjr.2021.0170 Text en Copyright © 2021 The Korean Society of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technology, Experiment, and Physics Kim, Sungchul Cho, Sungman Cho, Kyungjin Seo, Jiyeon Nam, Yujin Park, Jooyoung Kim, Kyuri Kim, Daeun Hwang, Jeongeun Yun, Jihye Jang, Miso Lee, Hyunna Kim, Namkug An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title | An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title_full | An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title_fullStr | An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title_full_unstemmed | An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title_short | An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research |
title_sort | open medical platform to share source code and various pre-trained weights for models to use in deep learning research |
topic | Technology, Experiment, and Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628158/ https://www.ncbi.nlm.nih.gov/pubmed/34719891 http://dx.doi.org/10.3348/kjr.2021.0170 |
work_keys_str_mv | AT kimsungchul anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT chosungman anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT chokyungjin anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT seojiyeon anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT namyujin anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT parkjooyoung anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimkyuri anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimdaeun anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT hwangjeongeun anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT yunjihye anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT jangmiso anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT leehyunna anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimnamkug anopenmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimsungchul openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT chosungman openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT chokyungjin openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT seojiyeon openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT namyujin openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT parkjooyoung openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimkyuri openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimdaeun openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT hwangjeongeun openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT yunjihye openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT jangmiso openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT leehyunna openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch AT kimnamkug openmedicalplatformtosharesourcecodeandvariouspretrainedweightsformodelstouseindeeplearningresearch |