| 1. |
- Angelis, Stavros, et al.
(author)
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Research Community Evaluation Report : Europeana Cloud Deliverable 1.7
- 2016
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Reports (other academic/artistic)abstract
- This report deals with three Evaluation Workshops organized by ATHENA R.C that took place as part of research undertaken in Work Package 1 of the Europeana Cloud (eCloud) project (2013-16). The workshops were linked to WP3 iterative development cycle, and intended to provide feedback regarding the usefulness, as against usability, of tools and service prototypes within Europeana Cloud and their fitness-for-purpose with regard to the requirements analysis and user-centred design of Europeana Research.
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| 2. |
- Angelis, Stavros, et al.
(author)
-
User Requirements Analysis and Case Studies Report. Content Strategy Report. : Europeana Cloud Deliverable 1.3 and 1.6: User Requirements Analysis and Case Studies Report (1.3) and Content Strategy Report (1.6)
- 2015
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Reports (other academic/artistic)abstract
- The present Deliverable (1.3) comprises of two joint reports: former Deliverable 1.3 (User Requirements and Case Studies report) and Deliverable 1.6 (Content Strategy Report). As a product of a multi-scale, interdisciplinary effort, Deliverable 1.3 (User Requirements and Case Studies report / Content Strategy Report) employs a multi-faceted approach to make sense of the information needs and behaviour of Humanities and Social Sciences researchers both within and outside the Europeana ecosystem, while achieving profound understanding of the ways these communities interact with existing Europeana content and metadata. Through extensive and widely-levelled empirical research (Case Studies, Web Survey, Interviews, Focus Groups) complimented by thorough desk research (Literature review, study of particular thematic areas), and building on work previously conducted in the context of other Digital Humanities Research Infrastructures (DARIAH, EHRI, ARIADNE, NeDiMAH) Work Package 1 managed to reach a long list of non-prioritized User Requirements as well as a set of flexible Content Recommendations for the upcoming development of Europeana Research.
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| 3. |
- Gavrilis, Dimitris, et al.
(author)
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A One-Class Approach to Cardiotocogram Assessment
- 2015
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In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - Piscataway, NJ : IEEE Communications Society. - 9781424492718 ; , s. 518-521
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Conference paper (peer-reviewed)abstract
- Cardiotocogram (CTG) is the most widely used means for the assessment of fetal condition. CTG consists of two traces one depicting the Fetal Heart Rate (FHR), and the other the Uterine Contractions (UC) activity. Many automatic methods have been proposed for the interpretation of the CTG. Most of them rely either on a binary classification approach or on a multiclass approach to come up with a decision about the class that the tracing belongs to. This work investigates the use of a one-class approach to the assessment of CTGs building a model only for the healthy data. The preliminary results are promising indicating that normal traces could be used as part of an automatic system that can detect deviations from normality.
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| 4. |
- Gavrilis, Dimitris, et al.
(author)
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An Inelligent Assistant for Physicians
- 2016
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In: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, 17-20 August 2016. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 2586-2589
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Conference paper (peer-reviewed)abstract
- This paper presents a software tool developed for assisting physicians during an examination process. The tool consists of a number of modules with the aim to make the examination process not only quicker but also fault proof moving from a simple electronic medical records management system towards an intelligent assistant for the physician. The intelligent component exploits users inputs as well as well established standards to line up possible suggestions for filling in the examination report. As the physician continues using it, the tool keeps extracting new knowledge. The architecture of the tool is presented in brief while the intelligent component which builds upon the notion of multilabel learning is presented in more detail. Our preliminary results from a real test case indicate that the performance of the intelligent module can reach quite high performance without a large amount of data.
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| 5. |
- Georgoulas, Georgios, et al.
(author)
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An ordinal classification approach for CTG categorization
- 2017
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In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - Piscataway, NJ : IEEE. - 9781509028092 ; , s. 2642-2645
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Conference paper (peer-reviewed)abstract
- Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.
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| 6. |
- Karvelis, Petros, et al.
(author)
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Topic recommendation using Doc2Vec
- 2018
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Conference paper (peer-reviewed)abstract
- The ever-increasing number of electronic content stored in digital libraries requires a significant amount of effort in cataloguing and has led to self-deposit solutions where the authors submit and publish their own digital records. Even in self-deposit, going through the abstract and assigning subject terms or keywords is a time consuming and expensive process, yet crucial for the metadata quality of the record that affects retrieval. Therefore, an automatic, or even a semi-automatic process that can recommend topics for a new entry is of huge practical value. A system that can address that has to rely basically on two components, one component for efficiently representing the relevant information of the new document and one component for recommending an appropriate set of topics based on the representation of the previous stage. In this work, different candidate solutions for both components are investigated and compared. For the first stage both distributed Document to Vector (doc2vec) and conventional Bag of Words (BoW) components are employed, while for the latter two different transformation approaches from the field of multi-label classification are compared. For the comparison, a collection of Ph.D. abstracts (~19000 documents) from the MIT Libraries Dspace repository is used suggesting that different combinations can provide high quality solutions.
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