ABSTRACT
In the field of cancer genomics, the broad availability of genetic information provided by advanced sequencing technologies needs to be fast and efficiently analyzed using Artificial intelligence approaches and interpreted in the context of additional characteristics from clinical records or molecular knowledge summarized in pathway databases. Cancer is a chronic disease, naturally making it coincide with other diseases. Advanced methods are needed to first retrieve the clinical information from the records, and thus associate with the multilevel omics data variables and further evaluate disease comorbidities. Further, one needs to transform big data into a clinically actionable source of information, e.g. evidence-based clinical recommendations. The unsolved challenge in cancer research and in clinics is integrating together various and permanently evolving types of data. Multiple diseases in a patient will require very thoughtful treatment design, probably involving drug repositioning.
