Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data.
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| Title: | Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data. |
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| Authors: | Rothstock, Stephan1, rothstock@gfai.de, Weiss, Hans-Rudolf2, Krueger, Daniel1, Paul, Lothar1 |
| Source: | Medical & Biological Engineering & Computing; 2020, Vol. 58 Issue 12, p2953-2962, 10p, 2 Color Photographs, 2 Diagrams, 2 Charts, 1 Graph |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 147105101 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11517-020-02258-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 2953 Titles: – TitleFull: Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rothstock, Stephan – PersonEntity: Name: NameFull: Weiss, Hans-Rudolf – PersonEntity: Name: NameFull: Krueger, Daniel – PersonEntity: Name: NameFull: Paul, Lothar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: 2020 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 01400118 Numbering: – Type: volume Value: 58 – Type: issue Value: 12 Titles: – TitleFull: Medical & Biological Engineering & Computing Type: main |
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