Four Different Artificial Intelligence Models<i>Versus</i>Logistic Regression to Enhance the Diagnostic Accuracy of Fecal Immunochemical Test in the Detection of Colorectal Carcinoma in a Screening Setting
AI models outperformed conventional LR and non-AI diagnostic features in improving FIT-based CRC screening. This is the first study to show that combining clinical data with FIT results in AI frameworks can significantly improve diagnostic accuracy in CRC screening.
Authors
- Kai Kaarniranta (ORCID: https://orcid.org/0000-0003-2600-8679)
- Tuomas A. Selander (ORCID: https://orcid.org/0000-0002-0070-8565)
- Matti J. Eskelinen (ORCID: https://orcid.org/0000-0002-6282-9725)
- Denise Peixoto Guimarães (ORCID: https://orcid.org/0000-0002-0568-7038)
- Karí Syrjänen (ORCID: https://orcid.org/0000-0001-7180-7491)
- MAARET ESKELINEN
Institutions
- University of Eastern Finland (FI)
- Kuopio University Hospital (FI)
- Hospital de Câncer de Barretos (BR)
Publication Details
- Journal
- Anticancer Research
- Published
- 2025-05-27
- DOI
- https://doi.org/10.21873/anticanres.17619
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- Pohjois-Savon Rahasto