By M. Elena Renda, Miroslav Bursa, Andreas Holzinger, Sami Khuri

This ebook constitutes the refereed complaints of the sixth foreign convention on details know-how in Bio- and clinical Informatics, ITBAM 2015, held in Valencia, Spain, in September 2015, along side DEXA 2015.

The nine revised lengthy papers offered including 1 poster paper have been conscientiously reviewed and chosen from 15 submissions. The papers handle the subsequent issues: clinical terminology and medical strategies and desktop studying in biomedicine.

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Extra info for Information Technology in Bio- and Medical Informatics: 6th International Conference, ITBAM 2015, Valencia, Spain, September 3-4, 2015, Proceedings

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G. [32]). – how to explore other sentiment anaysis methods, for instance combining lexical- and machine learning- based methods as suggested in [10], in order to improve the effectiveness of the proposed approach Using Twitter Data and Sentiment Analysis to Study Diseases Dynamics 23 – to gather a larger number of tweets (for instance, over a year or more) even in different geographical areas, to validate our proposal – to more deeply explore SNOMED-CT, for instance by exploiting relationships between concepts for a more effective health-related tweets extraction.

For these reasons, in this paper we propose an approach, mainly based on Open Data and Open Software, which can be easily adaptable to existing clinical information systems in order to verify the appropriateness of laboratory test requests. Particular attention has been posed to sensitive information, which are mainly protected by applying proper anonymization techniques. The paper is organised as follows: after the introduction in Sects. 1 and 2 presents background and related works in the field of clinical appropriateness looking for potential correlated studies.

In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 702–707, April 2011 2. : Predicting the future with social media. 5699 (2010). 5699 3. : A survey of techniques for event detection in twitter. Comput. Intell. 31(1), 132–164 (2015) 4. : Modern Information Retrievial. ACM Press, Seattle (1999) 5. : Contestualizzazione spaziale di informazioni medico scientifiche tramite sensori sociali. DIEEI - Internal, Report (2015) 6. : Uniqueness of medical data mining. Artif.

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