Performance comparison and future perspectives of deep learning and classical machine learning in bone tumor applications: a systematic review (2019-2025).
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| Title: | Performance comparison and future perspectives of deep learning and classical machine learning in bone tumor applications: a systematic review (2019-2025). |
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| Authors: | Qiao Y; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. yu.qiao@tum.de., Eisfeld C; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany., von Eisenhart-Rothe R; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany., Hinterwimmer F; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.; Institute for AI and Informatics in Medicine, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany. |
| Source: | BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2026 Feb 24; Vol. 26 (1). Date of Electronic Publication: 2026 Feb 24. |
| Publication Type: | Systematic Review; Journal Article; Comparative Study |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41735994 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Performance comparison and future perspectives of deep learning and classical machine learning in bone tumor applications: a systematic review (2019-2025). – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Qiao+Y%22">Qiao Y</searchLink>; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. yu.qiao@tum.de.<br /><searchLink fieldCode="AU" term="%22Eisfeld+C%22">Eisfeld C</searchLink>; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22von+Eisenhart-Rothe+R%22">von Eisenhart-Rothe R</searchLink>; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Hinterwimmer+F%22">Hinterwimmer F</searchLink>; Department of Orthopaedics and Sports Orthopaedics, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.; Institute for AI and Informatics in Medicine, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101088682%22">BMC medical informatics and decision making</searchLink> [BMC Med Inform Decis Mak] 2026 Feb 24; Vol. 26 (1). <i>Date of Electronic Publication: </i>2026 Feb 24. – Name: TypePub Label: Publication Type Group: TypPub Data: Systematic Review; Journal Article; Comparative Study – 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>101088682 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1472-6947 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214726947%22">14726947 </searchLink><i>NLM ISO Abbreviation: </i>BMC Med Inform Decis Mak <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41735994 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1186/s12911-026-03401-8 Languages: – Code: eng Text: English Titles: – TitleFull: Performance comparison and future perspectives of deep learning and classical machine learning in bone tumor applications: a systematic review (2019-2025). Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Qiao Y – PersonEntity: Name: NameFull: Eisfeld C – PersonEntity: Name: NameFull: von Eisenhart-Rothe R – PersonEntity: Name: NameFull: Hinterwimmer F IsPartOfRelationships: – BibEntity: Dates: – D: 24 M: 02 Text: 2026 Feb 24 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1472-6947 Numbering: – Type: volume Value: 26 – Type: issue Value: 1 Titles: – TitleFull: BMC medical informatics and decision making Type: main |
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