Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future.

ABSTRACT: With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. It has become critical to explore how machine learning and specifically deep learning methods can be exploited to analyse healthcare data. A major limitation of existing methods has been the focus on grid-like data; however, the structure of physiological recordings are often irregular and unordered, which makes it difficult to conceptualise them as a matrix. As such, graph neural networks have attracted significant attention by exploiting implicit information that resides in a biological system, with interacting nodes connected by edges whose weights can be determined by either temporal associations or anatomical junctions. In this survey, we thoroughly review the different

SUBMITTER: Ahmedt-Aristizabal D 

PROVIDER: S-EPMC8309939 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature