Employing machine learning to enhance fracture recovery insights through gait analysis.
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| Title: | Employing machine learning to enhance fracture recovery insights through gait analysis. |
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| Authors: | Rezapour M; Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA., Seymour RB; Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute and Wake Forest University School of Medicine, Charlotte, North Carolina, USA., Sims SH; Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute and Wake Forest University School of Medicine, Charlotte, North Carolina, USA., Karunakar MA; Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute and Wake Forest University School of Medicine, Charlotte, North Carolina, USA., Habet N; Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute and Wake Forest University School of Medicine, Charlotte, North Carolina, USA., Gurcan MN; Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA. |
| Source: | Journal of orthopaedic research : official publication of the Orthopaedic Research Society [J Orthop Res] 2024 Aug; Vol. 42 (8), pp. 1748-1761. Date of Electronic Publication: 2024 Apr 10. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley Country of Publication: United States NLM ID: 8404726 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1554-527X (Electronic) Linking ISSN: 07360266 NLM ISO Abbreviation: J Orthop Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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