Redesigning EHRs and Clinical Decision Support Systems for the Precision Medicine Era
MAGLOGIANNIS I.1, BILLIRIS A.2, KARANIKAS H.2, VALAVANIS I.3, PAPADODIMA O.3, CHATZIIONNOU A.3 & GOUDAS T.1
1University of Piraeus, Dept. of Digital Systems
3National Hellenic Research Foundation
In this work we present a distributed Health Record System Architecture, capable of integrating and duly accommodating the processing of heterogeneous, multi-layered (omics, histological images and clinical) data concerning the multi-angled description and management of melanoma patients. The proposed solution comprises a novel design of a layered analytical framework as an expansion of current EHR systems, which may integrate EHR data, high-volume molecular -omic data, imaging data as well as relevant clinical observations.
The case study used is in the field of dermatology, where we attempt to combine the multilayered information for the early detection of skin cancer. The specific architecture, aspires to lower the barrier for the introduction of personalized therapeutic approaches, in the 21st century in the context of precision medicine. The adopted schema, presumes that through the massive integration of multi-layered, voluminous data, describing the disease state at various organizational scales and the parallel processing of those streams, either alone or in conjunction with the others, significant advancement and speed up will occur concerning the quality and output of medical diagnostic tasks or patient management overall, thus paving the way for the introduction of personalized approaches in the therapeutic course.
The paper describes in detail the technical issues of implementation along with an initial evaluation and discussion.
“16 International Conference for Engineering Applications of Neural Networks (EANN), Rhodes, September, 2015”