The sarcopenia artificial intelligence diagnostic decision support system (SAID DSS) - a multimodal deep learning model.
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| Title: | The sarcopenia artificial intelligence diagnostic decision support system (SAID DSS) - a multimodal deep learning model. |
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| Authors: | Brockhattingen KK; Geriatric Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark. Kristoffer.k.brockhattingen@rsyd.dk.; Department of Geriatric Medicine, Odense University Hospital, Svendborg, Denmark. Kristoffer.k.brockhattingen@rsyd.dk.; Department of Geriatric Medicine, Odense University Hospital, Odense, Denmark. Kristoffer.k.brockhattingen@rsyd.dk.; Sarcopenia Through Ultrasound (SARCUS) working group, European Union Geriatric Medicine Society and University of Antwerp, Antwerp, Belgium. Kristoffer.k.brockhattingen@rsyd.dk., Karlsson EH; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark., Bielefeldt TBR; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark., Naemi A; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark.; Nordcee, Department of Biology, University of Southern Denmark, Sønderborg, Denmark., Andersen-Ranberg K; Geriatric Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.; Department of Geriatric Medicine, Odense University Hospital, Odense, Denmark.; Sarcopenia Through Ultrasound (SARCUS) working group, European Union Geriatric Medicine Society and University of Antwerp, Antwerp, Belgium., Moradbeiki P; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark., Ebrahimi A; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark., Wiil UK; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Sønderborg, Denmark. |
| Source: | BMC geriatrics [BMC Geriatr] 2026 Jan 26; Vol. 26 (1). Date of Electronic Publication: 2026 Jan 26. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 100968548 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2318 (Electronic) Linking ISSN: 14712318 NLM ISO Abbreviation: BMC Geriatr Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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