The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data
Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developments will lead to significant improvements in patie...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Public Library of Science
2019
|
| Online Access: | http://hdl.handle.net/1721.1/120809 https://orcid.org/0000-0002-5676-7898 |
| _version_ | 1811082508129796096 |
|---|---|
| author | Citi, Luca Ghassemi, Marzyeh Celi, Leo Anthony G. Pollard, Tom Joseph |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Citi, Luca Ghassemi, Marzyeh Celi, Leo Anthony G. Pollard, Tom Joseph |
| author_sort | Citi, Luca |
| collection | MIT |
| description | Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developments will lead to significant improvements in patient care. Like many academic disciplines, however, progress is hampered by lack of code and data sharing. In bringing together this PLOS ONE collection on machine learning in health and biomedicine, we sought to focus on the importance of reproducibility, making it a requirement, as far as possible, for authors to share data and code alongside their papers. |
| first_indexed | 2024-09-23T12:04:32Z |
| format | Article |
| id | mit-1721.1/120809 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T12:04:32Z |
| publishDate | 2019 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/1208092022-10-01T07:59:14Z The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data Citi, Luca Ghassemi, Marzyeh Celi, Leo Anthony G. Pollard, Tom Joseph Massachusetts Institute of Technology. Institute for Medical Engineering & Science Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology Celi, Leo Anthony G. Pollard, Tom Joseph Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developments will lead to significant improvements in patient care. Like many academic disciplines, however, progress is hampered by lack of code and data sharing. In bringing together this PLOS ONE collection on machine learning in health and biomedicine, we sought to focus on the importance of reproducibility, making it a requirement, as far as possible, for authors to share data and code alongside their papers. 2019-03-07T18:34:14Z 2019-03-07T18:34:14Z 2019-01 2019-03-07T15:54:40Z Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/120809 Celi, Leo A., Luca Citi, Marzyeh Ghassemi, and Tom J. Pollard. “The PLOS ONE Collection on Machine Learning in Health and Biomedicine: Towards Open Code and Open Data.” Edited by Leonie Anna Mueck. PLOS ONE 14, no. 1 (January 15, 2019): e0210232. © 2019 Celi et al. https://orcid.org/0000-0002-5676-7898 http://dx.doi.org/10.1371/journal.pone.0210232 PLOS ONE Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | Citi, Luca Ghassemi, Marzyeh Celi, Leo Anthony G. Pollard, Tom Joseph The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title | The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title_full | The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title_fullStr | The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title_full_unstemmed | The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title_short | The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data |
| title_sort | plos one collection on machine learning in health and biomedicine towards open code and open data |
| url | http://hdl.handle.net/1721.1/120809 https://orcid.org/0000-0002-5676-7898 |
| work_keys_str_mv | AT citiluca theplosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT ghassemimarzyeh theplosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT celileoanthonyg theplosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT pollardtomjoseph theplosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT citiluca plosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT ghassemimarzyeh plosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT celileoanthonyg plosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata AT pollardtomjoseph plosonecollectiononmachinelearninginhealthandbiomedicinetowardsopencodeandopendata |