A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas.
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| Title: | A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas. |
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| Authors: | Lin S; School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, 85281, AZ, USA., Wang C; Department of Health Sciences Research, Mayo Clinic, Rochester, 55905, MN, USA., Zarei S; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA., Bell DA; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA., Kerr SE; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA., Runger GC; School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, 85281, AZ, USA.; Department of Biomedical Informatics, Arizona State University, Scottsdale, 85259, AZ, USA., Kocher JA; Department of Health Sciences Research, Mayo Clinic, Rochester, 55905, MN, USA. kocher.jeanpierre@mayo.edu. |
| Source: | BMC genomics [BMC Genomics] 2018 Nov 27; Vol. 19 (1), pp. 841. Date of Electronic Publication: 2018 Nov 27. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 30482155 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Lin+S%22">Lin S</searchLink>; School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, 85281, AZ, USA.<br /><searchLink fieldCode="AU" term="%22Wang+C%22">Wang C</searchLink>; Department of Health Sciences Research, Mayo Clinic, Rochester, 55905, MN, USA.<br /><searchLink fieldCode="AU" term="%22Zarei+S%22">Zarei S</searchLink>; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA.<br /><searchLink fieldCode="AU" term="%22Bell+DA%22">Bell DA</searchLink>; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA.<br /><searchLink fieldCode="AU" term="%22Kerr+SE%22">Kerr SE</searchLink>; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, 55905, MN, USA.<br /><searchLink fieldCode="AU" term="%22Runger+GC%22">Runger GC</searchLink>; School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, 85281, AZ, USA.; Department of Biomedical Informatics, Arizona State University, Scottsdale, 85259, AZ, USA.<br /><searchLink fieldCode="AU" term="%22Kocher+JA%22">Kocher JA</searchLink>; Department of Health Sciences Research, Mayo Clinic, Rochester, 55905, MN, USA. kocher.jeanpierre@mayo.edu. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22100965258%22">BMC genomics</searchLink> [BMC Genomics] 2018 Nov 27; Vol. 19 (1), pp. 841. <i>Date of Electronic Publication: </i>2018 Nov 27. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22BioMed+Central%22">BioMed Central </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>100965258 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1471-2164 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214712164%22">14712164 </searchLink><i>NLM ISO Abbreviation: </i>BMC Genomics <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=30482155 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1186/s12864-018-5177-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 841 Titles: – TitleFull: A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lin S – PersonEntity: Name: NameFull: Wang C – PersonEntity: Name: NameFull: Zarei S – PersonEntity: Name: NameFull: Bell DA – PersonEntity: Name: NameFull: Kerr SE – PersonEntity: Name: NameFull: Runger GC – PersonEntity: Name: NameFull: Kocher JA IsPartOfRelationships: – BibEntity: Dates: – D: 27 M: 11 Text: 2018 Nov 27 Type: published Y: 2018 Identifiers: – Type: issn-electronic Value: 1471-2164 Numbering: – Type: volume Value: 19 – Type: issue Value: 1 Titles: – TitleFull: BMC genomics Type: main |
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