A Decision Tree Editor for Game Development: Applications in Breast Cancer Diagnosis and Treatment
Abstract
Introduction: This thesis presents NEED, an original decision tree editor designed for creating interactive games and applications, with emphasis on flexibility and interoperability. Objective: To develop a generic tool for dynamic modeling of decisions and data, with standardized export for game engine integration. Methodology: The editor was implemented and applied across three domains (legal, clinical, and narrative). Two serious games were developed with health specialists: Cancer: Now What? (diagnosis) and CancerSM (treatment). Results: The games validated NEED’s effectiveness in adaptive logic, emotional integration, and scientific grounding. JSON export ensured cross-platform compatibility. The editor proved to be a robust tool for decision support, simulation, and personalized learning, with technical, scientific, and social impact.
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