Lessons from the Development and Deployment of an Interactive Oncological Risk Estimator.

Authors

Nafiul Nipu, L V van Dijk, Guadalupe Canahuate, C David Fuller, G Elisabeta Marai

Published in

... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare. Volume 2025. Pages 29-35. Nov 02, 2025. Epub Dec 23, 2025.

Abstract

In the precision medicine paradigm, oncological treatment leverages complex ensemble datasets of similar patients to estimate the outcomes for a current patient. A key challenge is developing and deploying easy-to-understand AI predictive models for the outcomes of a specific patient, based on patient data from multiple institutions. We describe the lessons learned from the development and deployment of an interactive dashboard to support the analysis of individual head and neck cancer patient outcomes based on cohort data. As required by the project, the dashboard design aims to handle a large client base. The dashboard combines an AI solution with a multi-view interface featuring domain-specific plots to facilitate the visual analysis of patient outcomes and to quickly stratify new patients into risk groups. A year after the successful public deployment of the dashboard, we evaluate it with clinician domain experts. We report the feedback and we reflect on the lessons learned through this experience.

PMID:
42529378
Bibliographic data and abstract were imported from PubMed on 30 Jul 2026.

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