Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review.
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| Title: | Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review. |
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| Authors: | Salman LA; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar. loayasalman@gmail.com., Khatkar H; Royal London Hospital, Whitechapel, London, UK., Al-Ani A; Office of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan., Alzobi OZ; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar., Abudalou A; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar., Hatnouly AT; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar., Ahmed G; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar., Hameed S; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar., AlAteeq Aldosari M; Department of Orthopaedic Surgery, Surgical Specialty Center, Hamad General Hospital, Hamad Medical Corporation, PO Box 3050, Doha, Qatar. |
| Source: | European journal of orthopaedic surgery & traumatology : orthopedie traumatologie [Eur J Orthop Surg Traumatol] 2024 Feb; Vol. 34 (2), pp. 747-756. Date of Electronic Publication: 2023 Nov 27. |
| Publication Type: | Systematic Review; Journal Article |
| Journal Info: | Publisher: Springer-Verlag France Country of Publication: France NLM ID: 9518037 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1068 (Electronic) Linking ISSN: 16338065 NLM ISO Abbreviation: Eur J Orthop Surg Traumatol |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1432-1068 |
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| DOI: | 10.1007/s00590-023-03784-8 |