Deep learning in systems medicine.

Journal: Briefings in bioinformatics
Published Date: Mar 22, 2021

Abstract

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.

Authors

  • Haiying Wang
  • Estelle Pujos-Guillot
    metabolomic platform dedicated to metabolism studies in nutrition and health in the French National Research Institute for Agriculture, Food and Environment.
  • Blandine Comte
    French National Research Institute for Agriculture, Food and Environment.
  • Joao Luis de Miranda
    (ESTG/IPP) and a Researcher (CERENA/IST) in optimization methods and process systems engineering.
  • Vojtech Spiwok
    Molecular Modelling Researcher applying machine learning to accelerate molecular simulations.
  • Ivan Chorbev
    Faculty for Computer Science and Engineering, University Ss Cyril and Methodius in Skopje, North Macedonia working in the area of eHealth and assistive technologies.
  • Filippo Castiglione
    Institute for Applied Mathematics, National Research Council of Italy, Rome, Italy.
  • Paolo Tieri
    Institute for Applied Mathematics, National Research Council of Italy, Rome, Italy.
  • Steven Watterson
    computational biology at Ulster University.
  • Roisin McAllister
    Research Associate working in CTRIC, University of Ulster, Derry, and has worked in clinical and academic roles in the fields of molecular diagnostics and biomarker discovery.
  • Tiago de Melo Malaquias
    Research Associate in CTIRC, Derry, UK.
  • Massimiliano Zanin
    Centro de Tecnología Biomédica, Campus de Montegancedo, Universidad Politecnica de Madrid, Pozuelo de Alarcon, 28223, Madrid, Spain.
  • Taranjit Singh Rai
    Lecturer in cellular ageing at the Centre for Stratified Medicine. Dr Rai's research interests are in cellular senescence, which is thought to promote cellular and tissue ageing in disease, and the development of senolytic compounds to restrict this process.
  • Huiru Zheng
    School of Computing and Mathematics, University of Ulster, Jordanstown Campus, Shore Road, Newtownabbey BT37 0QB, UK.

Keywords

External Resources

Popular Topics
Recent Journals