Ovarian recurrence risk assessment using machine learning, clinical information, and serum protein levels to predict survival in high grade ovarian cancer
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Ovarian recurrence risk assessment using machine learning, clinical information, and serum protein levels to predict survival in high grade ovarian cancer ; volume:13 ; number:1 ; day:27 ; month:11 ; year:2023 ; pages:1-11 ; date:12.2023
Scientific reports ; 13, Heft 1 (27.11.2023), 1-11, 12.2023
- Urheber
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Mysona, David P.
Purohit, Sharad
Richardson, Katherine P.
Suhner, Jessa
Brzezinska, Bogna
Rungruang, Bunja
Hopkins, Diane
Bearden, Gregory
Higgins, Robert
Johnson, Marian
Bin Satter, Khaled
McIndoe, Richard
Ghamande, Sharad
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s41598-023-47983-z
- URN
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urn:nbn:de:101:1-2024021511313158659369
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:22 MESZ
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Beteiligte
- Mysona, David P.
- Purohit, Sharad
- Richardson, Katherine P.
- Suhner, Jessa
- Brzezinska, Bogna
- Rungruang, Bunja
- Hopkins, Diane
- Bearden, Gregory
- Higgins, Robert
- Johnson, Marian
- Bin Satter, Khaled
- McIndoe, Richard
- Ghamande, Sharad
- SpringerLink (Online service)
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