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Summarization from medical documents: a survey

2004; Elsevier BV; Volume: 33; Issue: 2 Linguagem: Inglês

10.1016/j.artmed.2004.07.017

1873-2860

Stergos Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos,

Biomedical Text Mining and Ontologies

The aim of this paper is to survey the recent work in medical documents summarization. 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. 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. 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.