Conceptual model of integrated approach for in silico knowledge data discovery for breast cancer diagnostics and precision therapy

Abstract

Breast cancer (BC) has the highest rate of cancer in women and causes the highest number of deaths, approximately 15% of all female cancer deaths. High incidence and mortality make it a leading socially significant disease. In practice, different specialists in different clinics carry out the different stages-screening, diagnosis, treatment and rehabilitation. With advances in medicine and the emergence of innovative precision medicine technologies, digital technology is gaining momentum. We propose conceptual model of integrated approach for combining and analyzing digital data from all stages using modern methods based on Knowledge Data Discovery. Collecting the data from all stages will facilitate early and accurate diagnosis, complex risk assessment, and will allow analysis of the significance of the various diagnostic and prognostic factors. The perspective is to design and implement scientific analytics workflow system for in silico knowledge data discovery and intelligent decision making based on the suggested integrated approach for breast cancer diagnostics and precision therapy recommendation.