Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-02-01
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| Series: | Insights into Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13244-023-01594-4 |
| _version_ | 1797274378907418624 |
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| author | Nikita Sushentsev Tristan Barrett Leonardo Rundo |
| author_facet | Nikita Sushentsev Tristan Barrett Leonardo Rundo |
| author_sort | Nikita Sushentsev |
| collection | DOAJ |
| first_indexed | 2024-03-07T14:57:31Z |
| format | Article |
| id | doaj.art-78a1da2db6d94ba78aaa807738e71b0b |
| institution | Directory Open Access Journal |
| issn | 1869-4101 |
| language | English |
| last_indexed | 2024-03-07T14:57:31Z |
| publishDate | 2024-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Insights into Imaging |
| spelling | doaj.art-78a1da2db6d94ba78aaa807738e71b0b2024-03-05T19:20:27ZengSpringerOpenInsights into Imaging1869-41012024-02-011511210.1186/s13244-023-01594-4Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic reviewNikita Sushentsev0Tristan Barrett1Leonardo Rundo2Department of Radiology, Addenbrooke’s Hospital and University of CambridgeDepartment of Radiology, Addenbrooke’s Hospital and University of CambridgeDepartment of Information and Electrical Engineering and Applied Mathematics (DIEM), University of Salernohttps://doi.org/10.1186/s13244-023-01594-4Artificial intelligenceMachine learningProstate cancer |
| spellingShingle | Nikita Sushentsev Tristan Barrett Leonardo Rundo Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review Insights into Imaging Artificial intelligence Machine learning Prostate cancer |
| title | Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review |
| title_full | Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review |
| title_fullStr | Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review |
| title_full_unstemmed | Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review |
| title_short | Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review |
| title_sort | reply to a letter to the editor on comparative performance of fully automated and semi automated artificial intelligence methods for the detection of clinically significant prostate cancer on mri a systematic review |
| topic | Artificial intelligence Machine learning Prostate cancer |
| url | https://doi.org/10.1186/s13244-023-01594-4 |
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