Kristian Samuelsson

Professor of Orthopaedic Surgery

Göteborgs Universitet

Sweden

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Kristian Samuelsson is a Professor of Orthopaedic Surgery at Göteborgs universitet Sahlgrenska Akademin, Sweden. His research primarily focuses on the application of artificial intelligence in musculoskeletal imaging, ACL reconstruction outcomes, and rehabilitation strategies. He has contributed extensively to studies examining graft failure rates, psychological responses post-surgery, and innovative treatments for knee osteoarthritis.

Articles (10)

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2025

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2025

Collaborators (4)

Johan Hogberg

University of Gothenburg

SWEDEN

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Robert Feldt

SWEDEN

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Michael T. Hirschmann

Section Head Knee Surgery

Kantonsspital Baselland (Bruderholz, Liestal, Laufen)

SWITZERLAND

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Rebecca Hamrin Senorski

University of Gothenburg

SWEDEN

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Kristian Samuelsson

Research Interests

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Articles (10)

Smaller hamstrings autograft size after primary ACL reconstruction is associated with higher odds for graft failure: A meta‐analysis on autografts sizes covering 46,268 patients

Rehabilitation alone after ACL injury yields greater limb symmetry but lower knee related self‐efficacy without limiting return to preinjury activity level

Greater psychological response and participation in knee‐strenuous activity 8 months after anterior cruciate ligament reconstruction in patients with generalised joint hypermobility who sustained a second anterior cruciate ligament injury: A cross‐sectional registry study

Artificial intelligence‐assisted analysis of musculoskeletal imaging—A narrative review of the current state of machine learning models

Risk Factors for Failure of Hip Arthroscopy in Patients With Borderline Dysplasia Include a Tönnis Angle ≥15°, Age ≥40 to 42 Years, Female Sex, Anterior Wall Index <0.35, Labral Debridement, and Preexisting Hip Osteoarthritis: A Systematic Review

The role of arthroscopy in intra‐articular adipose tissue‐derived mesenchymal stem cells for the treatment of early‐stage knee osteoarthritis: A bicentric retrospective comparative study

Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring

Artificial intelligence applications in the management of musculoskeletal disorders of the shoulder: A systematic review

Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review

Biomechanical comparison of tendon repair techniques: Bunnell suture leads in mode of failure and minimally invasive configuration in elongation

Collaborators (4)

Johan Hogberg

Robert Feldt

Michael T. Hirschmann

Rebecca Hamrin Senorski

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