par Morales Orcajo, Enrique;Stenti, Andrea 
Référence Digital Human Modeling and Medicine: The Digital Twin, Elsevier, page (331-359)
Publication Publié, 2022-01
Référence Digital Human Modeling and Medicine: The Digital Twin, Elsevier, page (331-359)
Publication Publié, 2022-01
Partie d'ouvrage collectif
| Résumé : | The variability between patients causes that standard treatments based on an “average patient” achieve low satisfaction rates after interventions. The improvement of these poor results involves moving from the one-treatment-fit-all to a subject-specific approach, the so-called personalized medicine. This personalization only can be achieved at a large scale by the use of digital technologies. In particular, the generation of patient digital twins, i.e., digital replicas of the patient's physiology that capture all its singularities. Digital twins will be used for better diagnosis, tailored treatments, and intervention risk reduction. Furthermore, a virtual population of patients grouped by pathology can be exploited for the experimentation of new surgical procedures, and the design and optimization of medical devices via in silico clinical trials. In this chapter, we explore the practical aspects of building foot digital twins and their clinical applications, to provide the human body modeler enough know-how to realize the human digital twin. |
