Mining the Medical and Patent Literature to Support Healthcare and Pharmacovigilance

Recent advancements in healthcare practices and the increasing use of information technology in the medical domain has lead to the rapid generation of free-text data in forms of scientific articles, e-health records, patents, and document inventories. This has urged the development of sophisticated information retrieval and information extraction technologies. A fundamental requirement for the automatic processing of biomedical text is the identification of information carrying units such as the concepts or named entities. In this context, this work focuses on the identification of medical disorders (such as diseases and adverse effects) which denote an important category of concepts in the medical text. Two methodologies were investigated in this regard and they are dictionary-based and machine learning-based approaches. Futhermore, the capabilities of the concept recognition techniques were systematically exploited to build a semantic search platform for the retrieval of e-health records and patents. The system facilitates conventional text search as well as semantic and ontological searches. Performance of the adapted retrieval platform for e-health records and patents was evaluated within open assessment challenges (i.e. TRECMED and TRECCHEM respectively) wherein the system was best rated in comparison to several other competing information retrieval platforms. Finally, from the medico-pharma perspective, a strategy for the identification of adverse drug events from medical case reports was developed. Qualitative evaluation as well as an expert validation of the developed system's performance showed robust results. In conclusion, this thesis presents approaches for efficient information retrieval and information extraction from various biomedical literature sources in the support of healthcare and pharmacovigilance. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. This can promote the literature-based knowledge discovery, improve the safety and effectiveness of medical practices, and drive the research and development in medical and healthcare arena

MORMED: towards a multilingual social networking platform facilitating medicine 2.0

The broad adoption of Web 2.0 tools has signalled a new era of "Medicine 2.0" in the field of medical informatics. The support for collaboration within online communities and the sharing of information in social networks offers the opportunity for new communication channels among patients, medical experts, and researchers. This paper introduces MORMED, a novel multilingual social networking and content management platform that exemplifies the Medicine 2.0 paradigm, and aims to achieve knowledge commonality by promoting sociality, while also transcending language barriers through automated translation. The MORMED platform will be piloted in a community interested in the treatment of rare diseases (Lupus or Antiphospholipid Syndrome)

On the Use of XML in Medical Imaging Web-Based Applications

The rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the Extensible Markup Language (XML) language in web-based applications that aid in diagnosis or treatment of patients, considering how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applicationsPeer ReviewedPostprint (author's final draft

On the Place of Text Data in Lifelogs, and Text Analysis via Semantic Facets

Current research in lifelog data has not paid enough attention to analysis of cognitive activities in comparison to physical activities. We argue that as we look into the future, wearable devices are going to be cheaper and more prevalent and textual data will play a more significant role. Data captured by lifelogging devices will increasingly include speech and text, potentially useful in analysis of intellectual activities. Analyzing what a person hears, reads, and sees, we should be able to measure the extent of cognitive activity devoted to a certain topic or subject by a learner. Test-based lifelog records can benefit from semantic analysis tools developed for natural language processing. We show how semantic analysis of such text data can be achieved through the use of taxonomic subject facets and how these facets might be useful in quantifying cognitive activity devoted to various topics in a person's day. We are currently developing a method to automatically create taxonomic topic vocabularies that can be applied to this detection of intellectual activity

Interoperable subject retrieval in a distributed multi-scheme environment : new developments in the HILT project

The HILT (HIgh-Level Thesaurus) project (http://hilt.cdlr.strath.ac.uk/), based primarily at the Centre for Digital Library Research (CDLR) (http://cdlr.strath.ac.uk/) at Strathclyde University in Glasgow is entering its fourth stage following the completion of Phases I (http://hilt.cdlr.strath.ac.uk/index1.html) and II (http://hilt.cdlr.strath.ac.uk/index2.html) and the Machine to Machine (M2M) Feasibility Study (http://hilt.cdlr.strath.ac.uk/hiltm2mfs/). HILT is funded by the Joint Information Systems Committee (JISC) in the United Kingdom (UK) to examine an issue of global significance - facilitating interoperability of subject descriptions in a distributed, cross-service retrieval environment where different services use different subject and classification schemes to describe content, making cross-searching by subject difficult. HILT Phase I determined that there was a community consensus in the UK in favour of using inter-scheme mapping to achieve interoperability between services using different schemes, an approach followed by several recent projects (Heery et al, 2001; Koch et al, 2001; MACS, 2005; Saeed and Chaudhury 2002). HILT Phase II chose a spine-based approach to mapping and chose the Dewey Decimal Classification (DDC) as the central scheme to which all other schemes would be mapped. It also built an illustrative pilot mapping service, based on an adaptation of the Wordmap (http://www.wordmap.com/) terminology-handling software and made a range of recommendations on issues requiring further research and ongoing development requirements

DCU@TRECMed 2012: Using ad-hoc baselines for domain-specific retrieval

This paper describes the first participation of DCU in the TREC Medical Records Track (TRECMed). We performed some initial experiments on the 2011 TRECMed data based on the BM25 retrieval model. Surprisingly, we found that the standard BM25 model with default parameters, performs comparable to the best automatic runs submitted to TRECMed 2011 and would have resulted in rank four out of 29 participating groups. We expected that some form of domain adaptation would increase performance. However, results on the 2011 data proved otherwise: concept-based query expansion decreased performance, and filtering and reranking by term proximity also decreased performance slightly. We submitted four runs based on the BM25 retrieval model to TRECMed 2012 using standard BM25, standard query expansion, result filtering, and concept-based query expansion. Official results for 2012 confirm that domain-specific knowledge does not increase performance compared to the BM25 baseline as applied by us

Semantic Integration of Cervical Cancer Data Repositories to Facilitate Multicenter Association Studies: The ASSIST Approach

The current work addresses the unifi cation of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifi es multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing fl exibility by allowing the formation of study groups “on demand” and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profi le) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the defi nition and representation of the disease’s medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains