Artificial Intelligence and Rectal Cancer: Beyond Images

• DOI: 10.20944/preprints202505.1887.v1
• Publication Date: 2025-05-26T01:43:13Z
• Authors: Tommaso Novellino; Carlotta Masciocchi; Andrada Mihaela T...; Calogero Casà; Giuditta Chiloiro; Angela Romano; Andrea Damiani; Giovanni Arcuri; Maria Antonietta ...; Vincenzo Valentini

Introduction. Cancer variability plus medical big data can be handled by artificial intelligence. Its models have different input types: images and many others (as numbers, predefined categories, free texts). The non image elements are as important images, per clinical practice literature. This article reviews such models, with component, applied use case to rectal cancer. Results Discussion. Secondary literature analysis shows all focusing on inputs only. Primary of interest include pure (only image) combined (both inputs. Non show significant performance. Combined frequently exhibit better behavior than their unimodal parts. Conclusion. To the best our knowledge, no focus inputs, either alone or images. components require instead substantial attention, in optimal research. Multimodality –beyond images– is important, cancer possibly other pathologies. Methods. Literature search was performed PubMed, without temporal limits, English, using ample keywords; for secondary literature, appropriate filters were employed.