The application of random forest-based models in prognostication of gastrointestinal tract malignancies: a systematic review
RF models, in terms of accuracy, performed better than the conventional approaches and provided better capabilities for clinical decision-making. Such models can increase the life quality and survival of patients by personalizing their treatment regimens for cancers of the GI tract. These models can, in a significant manner, raise patients' survival and quality of life through hastening clinical decision-making and providing personalized treatment options.
Authors
- Shahab Shayesteh
- Ahmad Shafizadeh
- Alireza Khodabande (ORCID: https://orcid.org/0000-0002-3957-7515)
- P Goudarzi (ORCID: https://orcid.org/0009-0002-0727-0559)
- H. Ashrafi (ORCID: https://orcid.org/0000-0003-0640-8958)
- Armin ZarinKhat (ORCID: https://orcid.org/0000-0002-1050-0661)
- Zhina Mohamadi (ORCID: https://orcid.org/0009-0007-6862-0379)
- Omid Bahrami (ORCID: https://orcid.org/0009-0005-4310-711X)
- Yalda Khodabandeh
- Kimia Pouyan
- Yasaman Aliyan
- Amirali Vaghari
Institutions
- Ahvaz Jundishapur University of Medical Sciences (IR)
- Guilan University of Medical Sciences (IR)
- Islamic Azad University Medical Branch of Tehran (IR)
- Kermanshah University of Medical Sciences (IR)
- Islamic Azad University, Ahvaz Branch (IR)
- Shahid Beheshti University of Medical Sciences (IR)
- Qazvin University of Medical Sciences (IR)
- Tehran University of Medical Sciences (IR)
- Shahroud University of Medical Sciences (IR)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-07-18
- DOI
- https://doi.org/10.3389/frai.2025.1517670
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00