Deep learning in systems medicine
Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM. ; This publication is based upon work from COST Action Open Multiscale Systems Medicine (OpenMultiMed, CA15120), supported by COST (European Cooperation in Science and Technology). COST is funded by the Horizon 2020 Framework Programme of the European Union. HZ and HYW are also supported by the MetaPlat(690998), SenseCare(690862) and STOP(823978) projects funded by H2020 RISE programme. FC and PT acknowledge the support of H2020 project iPC "individualized Paediatric Cure" (826121). Participation of V.S. in OpenMultiMed is supported by the Czech Ministry of Education, Youth and Sports (project LTC18074). JLM. thanks Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Portalegre (ESTG/IPP); and Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico (CERENA/IST) within the support of FCT-Fundação para a Ciência e a Tecnologia through the strategic project FCT-UIDB/04028/2020. MZ acknowledges the Spanish State Research Agency, through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D (MDM-2017-0711) and the funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (851255). The Northern Ireland Centre for Stratified Medicine has been financed by a grant awarded to AJ Bjourson under the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for Northern Ireland & the Northern Ireland Public Health Agency (HSC R&D). TSR also acknowledges funding from PHA R&D Division and the Western Health & Social Care. ; Peer reviewed