Early Evaluation of Cancer Progression and Treatments from Radiological Images Using Modeling and AI

Explore how mathematical modeling and AI can assist clinicians in monitoring solid cancer evolution through radiological images. Delve into the development of image-driven models, focusing on cases where longitudinal data is available. Examine the creation of an accurate model for describing meningioma natural growth. Learn about novel methods for personalizing models through data assimilation, recovering parameters from patients' radiological history, and building decision-support algorithms. Investigate the use of AI algorithms in cases where only single exams are available, including their application in automatic lesion segmentation. Discover the potential of combining mechanistic models and AI approaches to enhance prediction capabilities in cancer progression and treatment evaluation.