Enhanced Artificial Intelligence Methods for Liver Steatosis Assessment Using Machine Learning and Color Image Processing: Liver Color Project
Machine learning coupled with liver texture and color analysis of photographs taken with smartphones provides excellent accuracy for determining liver steatosis.
Authors
- Elizabeth Pando (ORCID: https://orcid.org/0000-0001-6898-5502)
- Concepción Gómez‐Gavara (ORCID: https://orcid.org/0000-0001-8312-3273)
- Jose Andrés Molino (ORCID: https://orcid.org/0000-0001-5360-1684)
- Miguel Ángel Cordobés
- Ernest Hidalgo (ORCID: https://orcid.org/0000-0002-4680-9580)
- R. Charco (ORCID: https://orcid.org/0000-0001-9709-6288)
- Cristina Dopazo (ORCID: https://orcid.org/0000-0001-6274-5911)
- Christopher Mazo
- Mar Dalmau (ORCID: https://orcid.org/0000-0002-2075-0912)
- Itxarone Bilbao (ORCID: https://orcid.org/0000-0002-7389-395X)
- Daniel Esono
- Ángela Bilbao
- Gemma Piella (ORCID: https://orcid.org/0000-0001-5236-5819)
- Javier Vázquez-Corral (ORCID: https://orcid.org/0000-0003-0414-7096)
- M. Caralt (ORCID: https://orcid.org/0000-0002-6110-8280)
- Laura Vidal (ORCID: https://orcid.org/0000-0003-3757-3323)
- Berta Benet‐Cugat
- María Teresa Salcedo
- Josa Prats
- M. Moya
Institutions
- Universitat Autònoma de Barcelona (ES)
- Universitat Pompeu Fabra (ES)
- Vall d'Hebron Institut de Recerca (ES)
- Vall d'Hebron Hospital Universitari (ES)
Publication Details
- Journal
- Clinical Transplantation
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1111/ctr.15465
- Citations
- 3
- Primary Topic
- Organ Transplantation Techniques and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 1.72
Funders
- Fundación Mutua Madrileña
- European Commission
- Generalitat de Catalunya
- Institució Catalana de Recerca i Estudis Avançats
- Instituto de Salud Carlos III
- European Regional Development Fund