title: Summarization from medical documents: a survey.
abstract: OBJECTIVE
  The aim of this paper is to survey the recent work in medical documents summarization.
  
  
  BACKGROUND
  During the last decade, documents summarization got increasing attention by the AI research community. More recently it also attracted the interest of the medical research community as well, due to the enormous growth of information that is available to the physicians and researchers in medicine, through the large and growing number of published journals, conference proceedings, medical sites and portals on the World Wide Web, electronic medical records, etc.
  
  
  METHODS
  This survey gives first a general background on documents summarization, presenting the factors that summarization depends upon, discussing evaluation issues and describing briefly the various types of summarization techniques. It then examines the characteristics of the medical domain through the different types of medical documents. Finally, it presents and discusses the summarization techniques used so far in the medical domain, referring to the corresponding systems and their characteristics.
  
  
  CONCLUSIONS
  The paper discusses thoroughly the promising paths for future research in medical documents summarization. It mainly focuses on the issue of scaling to large collections of documents in various languages and from different media, on personalization issues, on portability to new sub-domains, and on the integration of summarization technology in practical applications.
authors.affiliation: Software and Knowledge Engineering Laboratory, Institute of Informatics and Telecommunications, National Centre for Scientific Research (NCSR) Demokritos, 15310 Aghia Paraskevi Attikis, Athens, Greece. stergos@iit.demokritos.gr
authors.forename: Stergos
authors.initials: S
authors.lastname: Afantenos
authors.forename: Vangelis
authors.initials: V
authors.lastname: Karkaletsis
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Stamatopoulos
mesh_terms: D000043:Abstracting and Indexing / Q000145:classification / Q000379:methods; D019992:Databases as Topic; D004282:Documentation; D006801:Humans; D016247:Information Storage and Retrieval / Q000145:classification / Q000379:methods; D008490:Medical Informatics