The reproducibility crisis in the age of digital medicine
If anyone doubts the explosive growth of interest in digital medicine, consider a recent conference and workshop in Beijing, jointly organized by the People’s Liberation Army General Hospital and MIT Critical Data to showcase the opportunities and challenges of applying machine learning to the kind...
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| Other Authors: | |
| Format: | Article |
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Springer Nature
2020
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| Online Access: | https://hdl.handle.net/1721.1/124903 |
| _version_ | 1826217562698940416 |
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| author | Stupple, Aaron Singerman, David Celi, Leo Anthony G. |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Stupple, Aaron Singerman, David Celi, Leo Anthony G. |
| author_sort | Stupple, Aaron |
| collection | MIT |
| description | If anyone doubts the explosive growth of interest in digital medicine, consider a recent conference and workshop in Beijing, jointly organized by the People’s Liberation Army General Hospital and MIT Critical Data to showcase the opportunities and challenges of applying machine learning to the kind of data routinely collected during the provision of care.1 In person, 500 attendees heard a keynote and panels and participated in a health data hackathon. Online, however, the event was streamed to more than one million unique viewers. ©2020 [First paragraph] |
| first_indexed | 2024-09-23T17:05:39Z |
| format | Article |
| id | mit-1721.1/124903 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T17:05:39Z |
| publishDate | 2020 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | mit-1721.1/1249032022-10-03T10:23:00Z The reproducibility crisis in the age of digital medicine Stupple, Aaron Singerman, David Celi, Leo Anthony G. Massachusetts Institute of Technology. Institute for Medical Engineering & Science If anyone doubts the explosive growth of interest in digital medicine, consider a recent conference and workshop in Beijing, jointly organized by the People’s Liberation Army General Hospital and MIT Critical Data to showcase the opportunities and challenges of applying machine learning to the kind of data routinely collected during the provision of care.1 In person, 500 attendees heard a keynote and panels and participated in a health data hackathon. Online, however, the event was streamed to more than one million unique viewers. ©2020 [First paragraph] National Institute of Health NIBIB R01 (grant no. EB017205) 2020-04-28T18:40:23Z 2020-04-28T18:40:23Z 2019-01-29 Article http://purl.org/eprint/type/JournalArticle 2398-6352 https://hdl.handle.net/1721.1/124903 Stupple, Aaron, David Singerman, and Leo Anthony Celi, "The reproducibility crisis in the age of digital medicine." npj Digital Medicine 2, 1 (Jan. 2019): no. 2 doi 10.1038/s41746-019-0079-z ©2019 Author(s) 10.1038/s41746-019-0079-z npj Digital Medicine Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Springer Nature Nature |
| spellingShingle | Stupple, Aaron Singerman, David Celi, Leo Anthony G. The reproducibility crisis in the age of digital medicine |
| title | The reproducibility crisis in the age of digital medicine |
| title_full | The reproducibility crisis in the age of digital medicine |
| title_fullStr | The reproducibility crisis in the age of digital medicine |
| title_full_unstemmed | The reproducibility crisis in the age of digital medicine |
| title_short | The reproducibility crisis in the age of digital medicine |
| title_sort | reproducibility crisis in the age of digital medicine |
| url | https://hdl.handle.net/1721.1/124903 |
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