Figure 1.

The applications of artificial intelligence in clinical decision support systems. Starting from a pool of heterogeneous data from a large group of patients, such as methylated DNA analyses, scRNA-seq, and image analyses (i.e., histological and radiological), it is possible to divide patients into clusters using AI tools. Each patient cluster will be identified with a digital twin that will support and be supported by a biological twin which, through in vitro assays, will allow for the testing of pharmacological treatments better suited to the patient’s specific conditions.