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Background: Over the past 30 years, the international conference on Artificial Intelligence in MEdicine (AIME) has been organized at different venues across Europe every 2 years, establishing a forum for scientific exchange and creating an active research community. The Artificial Intelligence in Medicine journal has published theme issues with extended versions of selected AIME papers since 1998.Objectives: To review the history of AIME conferences, investigate its impact on the wider research field, and identify challenges for its future.Methods: We analyzed a total of 122 session titles to create a taxonomy of research themes and topics. We classified all 734 AIME conference papers published between 1985 and 2013 with this taxonomy. We also analyzed the citations to these conference papers and to 55 special issue papers.Results: We identified 30 research topics across 12 themes. AIME was dominated by knowledge engineering research in its first decade, while machine learning and data mining prevailed thereafter. Together these two themes have contributed about 51% of all papers. There have been eight AIME papers that were cited at least 10 times per year since their publication.Conclusions: There has been a major shift from knowledge-based to data-driven methods while the interest for other research themes such as uncertainty management, image and signal processing, and natural language processing has been stable since the early 1990s. AIME papers relating to guidelines and protocols are among the most highly cited. [ABSTRACT FROM AUTHOR]

Sustainable development as a concept that aims to enhance the quality of life without affecting environment has been in focus in European policies since the last decade of 20th century. The objectives of EU Sustainable Development Strategy (EU SDS) are grouped into ten thematic areas, where almost each theme has at least one headline and several operational sustainable development indicators (SDIs). A large number of SDIs is needed to evaluate all EU SDS goals, which imposes the use of multivariate data mining techniques. This paper presents an empirical study carried out to assess the sustainability performance of European countries using the differential multi criteria analysis (DMCA) technique. The PROMETHEE (Preference Ranking Organization MeTHod for Enrichment Evaluations) was applied on 38 headline and operational SDIs defined under the EU SDS. This DMCA was applied to 30 European countries over a 10-year period (2004–2014) with the aim to determine the theme specific, as well as, overall sustainability progress. The DMCA reveals that the majority of European countries have made progress in sustainability in the studied period, where Czech Republic, Germany, Hungary and Sweden, have enhanced their sustainability performance concerning all themes. There are only two countries, namely Greece and Ireland, which have not made overall progress in this period. Also, above the average progress has been made concerning social inclusion, sustainable transport, and climate change and energy, while in all other themes additional efforts should be made in order to ensure sustainable performance progress in future years. Although the progress in reducing uneven development between EU members has been made, after 2009 a positive trend can be observed only in a limited number of SDS themes. [ABSTRACT FROM AUTHOR]

Different programs of The European Science Foundation (ESF) have contributed significantly to connect researchers in Europe and beyond through several initiatives. This support was particularly relevant for the development of the areas related with extracting information from papers (text-mining) because it supported the field in its early phases long before it was recognized by the community. We review the historical development of text mining research and how it was introduced in bioinformatics. Specific applications in (functional) genomics are described like it''s integration in genome annotation pipelines and the support to the analysis of high-throughput genomics experimental data, and we highlight the activities of evaluation of methods and benchmarking for which the ESF programme support was instrumental. [Copyright &y& Elsevier]