Using a Disentangled Neural Network to Objectively Assess the Outcomes of Midfacial Surgery in Syndromic Craniosynostosis
Objective outcome evaluation, which encourages in-depth analysis and enhances decision-making, is essential for the progression of surgical practice. The authors demonstrate how artificial intelligence has the ability to improve our understanding of surgery and its effect on craniofacial morphology.
Authors
- Matthew J. Clarkson (ORCID: https://orcid.org/0000-0002-5565-1252)
- Connor S. Wagner
- Silvia Schievano (ORCID: https://orcid.org/0000-0003-2037-5339)
- Lara S. van de Lande (ORCID: https://orcid.org/0000-0003-2482-199X)
- David Dunaway (ORCID: https://orcid.org/0000-0001-5063-9943)
- Jesse A. Taylor (ORCID: https://orcid.org/0000-0003-2827-5471)
- Alexander Rickart (ORCID: https://orcid.org/0000-0002-9779-9503)
- Owase Jeelani (ORCID: https://orcid.org/0000-0002-3240-681X)
- Simone Foti
- Juling Ong (ORCID: https://orcid.org/0000-0003-2212-930X)
- Scott Paul P. Bartlett (ORCID: https://orcid.org/0009-0004-2310-3659)
- Jordan W. Swanson
Institutions
- Children's Hospital of Philadelphia (US)
- Great Ormond Street Hospital (GB)
- Erasmus MC (NL)
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences (GB)
- University College London (GB)
- Imperial College London (GB)
- Erasmus University Rotterdam (NL)
Publication Details
- Journal
- Plastic & Reconstructive Surgery
- Published
- 2024-08-20
- DOI
- https://doi.org/10.1097/prs.0000000000011686
- Citations
- 4
- Primary Topic
- Craniofacial Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.20
Funders
- Wellcome Trust
- NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
- National Institute for Health and Care Research
- Engineering and Physical Sciences Research Council