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(Field of Science):
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(Field of Science)
Ministry points: Help
| Year | Points | List |
|---|---|---|
| Year 2024 | 100 | Ministry scored journals list 2024 |
| Year | Points | List |
|---|---|---|
| 2024 | 100 | Ministry scored journals list 2024 |
| 2023 | 100 | Ministry Scored Journals List |
| 2022 | 100 | Ministry Scored Journals List 2019-2022 |
| 2021 | 100 | Ministry Scored Journals List 2019-2022 |
| 2020 | 100 | Ministry Scored Journals List 2019-2022 |
| 2019 | 100 | Ministry Scored Journals List 2019-2022 |
| 2018 | 30 | A |
| 2017 | 30 | A |
| 2016 | 30 | A |
| 2015 | 30 | A |
| 2014 | 30 | A |
| 2013 | 30 | A |
| 2012 | 30 | A |
| 2011 | 30 | A |
| 2010 | 32 | A |
Points CiteScore:
| Year | Points |
|---|---|
| Year 2023 | 6.4 |
| Year | Points |
|---|---|
| 2023 | 6.4 |
| 2022 | 6.4 |
| 2021 | 6.2 |
| 2020 | 6.3 |
| 2019 | 5.8 |
| 2018 | 6.2 |
| 2017 | 6 |
| 2016 | 5.7 |
| 2015 | 5.1 |
| 2014 | 4.7 |
| 2013 | 5.1 |
| 2012 | 5.9 |
| 2011 | 5.7 |
Impact Factor:
Sherpa Romeo:
Papers published in journal
Filters
total: 3
Catalog Journals
Year 2023
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A review of methods of blood supply to organs of the gastrointestinal tract. State of art
PublicationThe correct assessment of blood supply is essential to eliminate possible postoperative complications. Re-anastomosis of the gastrointestinal tract after its resection must be preceded by the analysis of blood supply to the anastomosed fragments. It is important that the blood supply assessment procedure is reliable but also non-absorbing and, if possible, short. It should also be possible to repeat the procedure due to the need...
Year 2022
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
Year 2006
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