Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach
In conclusion, this study highlights the potential of machine learning models, particularly Support Vector Machines (SVMs), in predicting successful weight loss after Sleeve bariatric surgery. The key predictive variables identified include biochemical markers, anthropometric measures, and psychological factors, emphasizing the multifactorial nature of postoperative weight loss outcomes.
Authors
- Beatriz Ramos Bachiller (ORCID: https://orcid.org/0000-0003-1769-0848)
- Isabel Herrera Montano (ORCID: https://orcid.org/0000-0003-0841-653X)
- Daniel Antonio de Luis (ORCID: https://orcid.org/0000-0002-1745-9315)
- Juan José López Gómez (ORCID: https://orcid.org/0000-0003-3144-343X)
- Isabel de la Torre Díez
- Manuel Fernández Domínguez
Institutions
- Universidad de Valladolid (ES)
Publication Details
- Journal
- Nutrients
- Published
- 2025-04-21
- DOI
- https://doi.org/10.3390/nu17081391
- Citations
- 1
- Primary Topic
- Bariatric Surgery and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.01