NornirNet: A Deep Learning Framework to Distinguish Benign from Malignant Type II Endoleaks After Endovascular Aortic Aneurysm Repair Using Preoperative Imaging.
Saved in:
| Title: | NornirNet: A Deep Learning Framework to Distinguish Benign from Malignant Type II Endoleaks After Endovascular Aortic Aneurysm Repair Using Preoperative Imaging. |
|---|---|
| Authors: | Andreoli, Francesco1 (AUTHOR), Mattiussi, Fabio2 (AUTHOR), Wasseh, Elias3 (AUTHOR), Leoncini, Andrea1,2 (AUTHOR), Ettorre, Ludovica1,2 (AUTHOR), Galafassi, Jacopo1,3 (AUTHOR), Ruffino, Maria Antonella2 (AUTHOR), Giovannacci, Luca1 (AUTHOR), Robaldo, Alessandro1 (AUTHOR), Prouse, Giorgio1 (AUTHOR) giorgio.prouse@eoc.ch |
| Source: | AI. Feb2026, Vol. 7 Issue 2, p57. 24p. |
| Database: | Academic Search Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: asn DbLabel: Academic Search Ultimate An: 192097548 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: NornirNet: A Deep Learning Framework to Distinguish Benign from Malignant Type II Endoleaks After Endovascular Aortic Aneurysm Repair Using Preoperative Imaging. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Andreoli%2C+Francesco%22">Andreoli, Francesco</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mattiussi%2C+Fabio%22">Mattiussi, Fabio</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wasseh%2C+Elias%22">Wasseh, Elias</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Leoncini%2C+Andrea%22">Leoncini, Andrea</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ettorre%2C+Ludovica%22">Ettorre, Ludovica</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Galafassi%2C+Jacopo%22">Galafassi, Jacopo</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ruffino%2C+Maria+Antonella%22">Ruffino, Maria Antonella</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Giovannacci%2C+Luca%22">Giovannacci, Luca</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Robaldo%2C+Alessandro%22">Robaldo, Alessandro</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Prouse%2C+Giorgio%22">Prouse, Giorgio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> giorgio.prouse@eoc.ch</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22AI%22">AI</searchLink>. Feb2026, Vol. 7 Issue 2, p57. 24p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192097548 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/ai7020057 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 57 Titles: – TitleFull: NornirNet: A Deep Learning Framework to Distinguish Benign from Malignant Type II Endoleaks After Endovascular Aortic Aneurysm Repair Using Preoperative Imaging. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Andreoli, Francesco – PersonEntity: Name: NameFull: Mattiussi, Fabio – PersonEntity: Name: NameFull: Wasseh, Elias – PersonEntity: Name: NameFull: Leoncini, Andrea – PersonEntity: Name: NameFull: Ettorre, Ludovica – PersonEntity: Name: NameFull: Galafassi, Jacopo – PersonEntity: Name: NameFull: Ruffino, Maria Antonella – PersonEntity: Name: NameFull: Giovannacci, Luca – PersonEntity: Name: NameFull: Robaldo, Alessandro – PersonEntity: Name: NameFull: Prouse, Giorgio IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 26732688 Numbering: – Type: volume Value: 7 – Type: issue Value: 2 Titles: – TitleFull: AI Type: main |
| ResultId | 1 |