Computer copilots for endoscopic diagnosis
Artificial intelligence (AI) tools for endoscopy are now entering clinical practice after demonstrating substantial improvements to polyp detection on colonoscopy. As this technology continues to mature, efforts to develop and validate a new frontier of possibilities—including diagnostic classificat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-022-00678-7 |
| _version_ | 1797642327000350720 |
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| author | James A. Diao Joseph C. Kvedar |
| author_facet | James A. Diao Joseph C. Kvedar |
| author_sort | James A. Diao |
| collection | DOAJ |
| description | Artificial intelligence (AI) tools for endoscopy are now entering clinical practice after demonstrating substantial improvements to polyp detection on colonoscopy. As this technology continues to mature, efforts to develop and validate a new frontier of possibilities—including diagnostic classification, risk stratification, and clinical outcomes assessment—are now underway. In npj Digital Medicine, scientists from Cosmo AI/Linkverse and collaborators report an extension to the first FDA-cleared AI tool for colonoscopy that goes beyond polyp detection to enable video-based diagnostic characterization. |
| first_indexed | 2024-03-11T13:58:27Z |
| format | Article |
| id | doaj.art-c4cf147afbf94ea6a153828abf056301 |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-11T13:58:27Z |
| publishDate | 2022-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-c4cf147afbf94ea6a153828abf0563012023-11-02T05:33:25ZengNature Portfolionpj Digital Medicine2398-63522022-09-01511210.1038/s41746-022-00678-7Computer copilots for endoscopic diagnosisJames A. Diao0Joseph C. Kvedar1Harvard Medical SchoolHarvard Medical SchoolArtificial intelligence (AI) tools for endoscopy are now entering clinical practice after demonstrating substantial improvements to polyp detection on colonoscopy. As this technology continues to mature, efforts to develop and validate a new frontier of possibilities—including diagnostic classification, risk stratification, and clinical outcomes assessment—are now underway. In npj Digital Medicine, scientists from Cosmo AI/Linkverse and collaborators report an extension to the first FDA-cleared AI tool for colonoscopy that goes beyond polyp detection to enable video-based diagnostic characterization.https://doi.org/10.1038/s41746-022-00678-7 |
| spellingShingle | James A. Diao Joseph C. Kvedar Computer copilots for endoscopic diagnosis npj Digital Medicine |
| title | Computer copilots for endoscopic diagnosis |
| title_full | Computer copilots for endoscopic diagnosis |
| title_fullStr | Computer copilots for endoscopic diagnosis |
| title_full_unstemmed | Computer copilots for endoscopic diagnosis |
| title_short | Computer copilots for endoscopic diagnosis |
| title_sort | computer copilots for endoscopic diagnosis |
| url | https://doi.org/10.1038/s41746-022-00678-7 |
| work_keys_str_mv | AT jamesadiao computercopilotsforendoscopicdiagnosis AT josephckvedar computercopilotsforendoscopicdiagnosis |