title: Models and Data Sources Used in Systems Medicine. A Systematic Literature Review.
abstract: BACKGROUND
  Systems medicine is a new approach for the development and selection of treatment strategies for patients with complex diseases. It is often referred to as the application of systems biology methods for decision making in patient care. For systems medicine computer applications, many different data sources have to be integrated and included into models. This is a challenging task for Medical Informatics since the approach exceeds traditional systems like Electronic Health Records. To prioritize research activities for systems medicine applications, it is necessary to get an overview over modelling methods and data sources already used in this field.
  
  
  OBJECTIVE
  We performed a systematic literature review with the objective to capture current use of 1) modelling methods and 2) data sources in systems medicine related research projects.
  
  
  METHODS
  We queried the MEDLINE and ScienceDirect databases for papers associated with the search term systems medicine and related terms. Papers were screened and assessed in full text in a two-step process according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines.
  
  
  RESULTS
  The queries returned 698 articles of which 34 papers were finally included into the study. A multitude of modelling approaches such as machine learning and network analysis was identified and classified. Since these approaches are also used in other domains, no methods specific for systems medicine could be identified. Omics data are the most widely used data types followed by clinical data. Most studies only include a rather limited number of data sources.
  
  
  CONCLUSIONS
  Currently, many different modelling approaches are used in systems medicine. Thus, highly flexible modular solutions are necessary for systems medicine clinical applications. However, the number of data sources included into the models is limited and most projects currently focus on prognosis. To leverage the potential of systems medicine further, it will be necessary to focus on treatment strategies for patients and consider a broader range of data.
authors: M
authors: M
authors: Gietzelt
authors: M
authors: M
authors: Löpprich
authors: C
authors: C
authors: Karmen
authors: P
authors: P
authors: Knaup
authors: Matthias Ganzinger, Heidelberg University, Institute of Medical Biometry and Informatics, Im Neuenheimer Feld 130.3, 69120 Heidelberg, Germany, E-mail: matthias.ganzinger@med.uni-heidelberg.de.
authors: M
authors: M
authors: Ganzinger
mesh_terms: D016247:Information Storage and Retrieval; D008962:Models, Theoretical; D013223:Statistics as Topic; D013597:Systems Analysis
keywords: Systems medicine; data sources; medical informatics; models; systematic literature review