In the LANTERN project, **Digital Human Avatars** (DHA) play a pivotal role as they serve as digital representations of patients. These avatars integrate various omics-based data (such as genomic information and quantitative imaging data) along with traditional clinical factors like age, sex, and TNM stage (a cancer staging system). The purpose of creating these DHAs is to develop accurate predictive models for managing lung cancer patients more effectively. The DHAs essentially allow for a more personalized approach to treatment, as they can help predict individual-specific responses to different treatments, provide feedback data for preventative healthcare strategies, and aid in managing patients’ quality of life. Additionally, the development and application of DHAs and their associated predictive models aim to improve the accuracy of diagnosis and enable complete personalization of treatment for lung cancer patients.
https://bmccancer.biomedcentral.com/articles/10.1186/s12885-023-10997-x