| 1. |
- AAl Abdulsalam, Abdulrahman, et al.
(författare)
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UtahBMI at SemEval-2016 Task 12 : Extracting Temporal Information from Clinical Text
- 2016
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Ingår i: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). - : Association for Computational Linguistics. ; , s. 1256-1262
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Konferensbidrag (refereegranskat)abstract
- The 2016 Clinical TempEval continued the 2015 shared task on temporal information extraction with a new evaluation test set. Our team, UtahBMI, participated in all subtasks using machine learning approaches with ClearTK (LIBLINEAR), CRF++ and CRFsuite packages. Our experiments show that CRF-based classifiers yield, in general, higher recall for multi-word spans, while SVM-based classifiers are better at predicting correct attributes of TIMEX3. In addition, we show that an ensemble-based approach for TIMEX3 could yield improved results. Our team achieved competitive results in each subtask with an F1 75.4% for TIMEX3, F1 89.2% for EVENT, F1 84.4% for event relations with document time (DocTimeRel), and F1 51.1% for narrative container (CONTAINS) relations.
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| 2. |
- Allvin, Helen, et al.
(författare)
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Characteristics of Finnish and Swedish intensive care nursing narratives : a comparative analysis to support the development of clinical language technologies
- 2011
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Ingår i: Journal of Biomedical Semantics. - 2041-1480. ; 2:S1, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Free text is helpful for entering information into electronic health records, but reusing it is a challenge. The need for language technology for processing Finnish and Swedish healthcare text is therefore evident; however, Finnish and Swedish are linguistically very dissimilar. In this paper we present a comparison of characteristics in Finnish and Swedish free-text nursing narratives from intensive care. This creates a framework for characterising and comparing clinical text and lays the groundwork for developing clinical language technologies. Methods: Our material included daily nursing narratives from one intensive care unit in Finland and one in Sweden. Inclusion criteria for patients were an inpatient period of least five days and an age of at least 16 years. We performed a comparative analysis as part of a collaborative effort between Finnish- and Swedish-speaking healthcare and language technology professionals that included both qualitative and quantitative aspects. The qualitative analysis addressed the content and structure of three average- sized health records from each country. In the quantitative analysis 514 Finnish and 379 Swedish health records were studied using various language technology tools. Results: Although the two languages are not closely related, nursing narratives in Finland and Sweden had many properties in common. Both made use of specialised jargon and their content was very similar. However, many of these characteristics were challenging regarding development of language technology to support producing and using clinical documentation. Conclusions: The way Finnish and Swedish intensive care nursing was documented, was not country or language dependent, but shared a common context, principles and structural features and even similar vocabulary elements. Technology solutions are therefore likely to be applicable to a wider range of natural languages, but they need linguistic tailoring. Availability: The Finnish and Swedish data can be found at: http://www.dsv.su.se/ hexanord/data/
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| 3. |
- Andrenucci, Andrea, et al.
(författare)
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Knowledge patterns for online health portal development
- 2019
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Ingår i: Health Informatics Journal. - : SAGE Publications. - 1460-4582 .- 1741-2811. ; 25:4, s. 1779-1799
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Tidskriftsartikel (refereegranskat)abstract
- This article describes the development and evaluation of a set of knowledge patterns that provide guidelines and implications of design for developers of mental health portals. The knowledge patterns were based on three foundations: 1) Knowledge integration of language technology approaches; 2) Experiments with language technology applications and 3) User studies of portal interaction. A mixed-methods approach was employed for the evaluation of the knowledge patterns: formative workshops with knowledge pattern experts and summative surveys with experts in specific domains. The formative evaluation improved the cohesion of the patterns. The results of the summative evaluation showed that the problems discussed in the patterns were relevant for the domain and that the knowledge embedded was useful to solve them. Ten patterns out of thirteen achieved an average score above 4.0, which is a positive result that leads us to conclude that they can be used as guidelines for developing health portals.
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| 4. |
- Andrenucci, Andrea, 1971-
(författare)
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Using Language Technology to Mediate Medical Information on Health Portals : User Studies and Experiments
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The World Wide Web has revolutionized our lifestyle, our economies and services within health care. Health care services are no longer provided only at specialist centers and at scheduled hours, but also through online tools that give health care consumers access to medical information, health records, medical counselling and peer support. Such tools and applications are generally available on larger web sites or gateways called health portals. A large majority of online medical information consumers are laypeople (i.e. non experts) who appreciate the possibility to submit their information needs in their own native language. The information retrieval process where information requests from users and retrieved documents/answers are in different languages is called cross-language information retrieval (CLIR). Mental health is one of the medical areas where some online applications have been successfully deployed in order to help people by providing in-depth medical information, counseling and advice. Despite the fact that online health portals are considered priority e-health tools for improving mental health, there are no formal knowledge instruments such as knowledge patterns that explicitly support the development of online health portals in the field of psychology/psychotherapy. The goal of this research is to produce and evaluate a set of knowledge patterns, for the development and implementation of cross-lingual online health portals aimed at information seekers without medical expertise in the domain of psychology and psychotherapy. The knowledge patterns synthetize results of three research foundations: 1) User studies of portal interaction, based on interviews and observations about how users experience health information online and personalized search 2) Knowledge integration of existing language technology approaches, and 3) Experiments with language technology applications, in the field of cross-lingual information retrieval/question-answering. The target groups of this research are developers, researchers and health care providers, i.e. people who are responsible for mediating medical information on online health portals for users without medical expertise. The chosen research framework is design science, i.e. the science that focuses on the study, development and evaluation of artefacts (objects that help people solve a practical problem). Typical examples of artefacts in IT are algorithms, software solutions and databases, but also objects such as processes or knowledge patterns. The developed and evaluated artefact in this research is a set of knowledge patterns for online health portal development. The developed artefact contains fourteen knowledge patterns covering the three research foundations. Formative (structured workshops) and summative (online survey) evaluation of the artefact indicate that the knowledge patterns are useful, relevant and adoptable to a large extent, they also provide further directions for development of online mental health portals. Developing portals with multilingual support and tailored interfaces has the potential of helping larger groups of citizens to access relevant medical information.
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| 5. |
- Bittar, A., et al.
(författare)
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Text classification to inform suicide risk assessment in electronic health records
- 2019
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Ingår i: 17th World Congress on Medical and Health Informatics, MEDINFO 2019. - : IOS Press. - 9781643680026 ; , s. 40-44
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Konferensbidrag (refereegranskat)abstract
- Assessing a patient's risk of an impending suicide attempt has been hampered by limited information about dynamic factors that change rapidly in the days leading up to an attempt. The storage of patient data in electronic health records (EHRs) has facilitated population-level risk assessment studies using machine learning techniques. Until recently, most such work has used only structured EHR data and excluded the unstructured text of clinical notes. In this article, we describe our experiments on suicide risk assessment, modelling the problem as a classification task. Given the wealth of text data in mental health EHRs, we aimed to assess the impact of using this data in distinguishing periods prior to a suicide attempt from those not preceding such an attempt. We compare three different feature sets, one structured and two text-based, and show that inclusion of text features significantly improves classification accuracy in suicide risk assessment.
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| 6. |
- Chapman, Wendy W., et al.
(författare)
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Extending the NegEx Lexicon for Multiple Languages
- 2013
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Ingår i: Proceedings of the 14th World Congress on Medical and Health Informatics. - : IOS Press. - 9781614992882 - 9781614992899 ; , s. 677-681
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Konferensbidrag (refereegranskat)abstract
- We translated an existing English negation lexicon (NegEx) to Swedish, French, and German and compared the lexicon on corpora from each language. We observed Zipf’s law for all languages, i.e., a few phrases occur a large number of times, and a large number of phrases occur fewer times. Negation triggers “no” and “not” were common for all languages; however, other triggers varied considerably. The lexicon is available in OWL and RDF format and can be extended to other languages. We discuss the challenges in translating negation triggers to other languages and issues in representing multilingual lexical knowledge.
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| 7. |
- Dalianis, Hercules, et al.
(författare)
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De-identifying Swedish Clinical Text - Refinement of a Gold Standard and Experiments with Conditional Random Fields
- 2009
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Ingår i: The 3rd International Symposium on Languages in Biology and Medicine. - Hyatt Regency, Seogwipo-si, Jeju Island, South Korea November 8-10, 2009 : Jong C. Park (KAIST, Korea) , Limsoon Wong (NUS, Singapore), See-Kiong Ng (NTU & I2R, Singapore).
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Konferensbidrag (refereegranskat)
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| 8. |
- Dalianis, Hercules, et al.
(författare)
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De-identifying Swedish clinical text - refinement of a gold standard and experiments with Conditional random fields
- 2010
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Ingår i: Journal of Biomedical Semantics. - : BioMed Central. - 2041-1480. ; 1:6
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Tidskriftsartikel (refereegranskat)abstract
- Background In order to perform research on the information contained in Electronic Patient Records (EPRs), access to the data itself is needed. This is often very difficult due to confidentiality regulations. The data sets need to be fully de-identified before they can be distributed to researchers. De-identification is a difficult task where the definitions of annotation classes are not self-evident. Results We present work on the creation of two refined variants of a manually annotated Gold standard for de-identification, one created automatically, and one created through discussions among the annotators. The data is a subset from the Stockholm EPR Corpus, a data set available within our research group. These are used for the training and evaluation of an automatic system based on the Conditional Random Fields algorithm. Evaluating with four-fold cross-validation on sets of around 4-6 000 annotation instances, we obtained very promising results for both Gold Standards: F-score around 0.80 for a number of experiments, with higher results for certain annotation classes. Moreover, 49 false positives that were verified true positives were found by the system but missed by the annotators. Conclusions Our intention is to make this Gold standard, The Stockholm EPR PHI Corpus, available to other research groups in the future. Despite being slightly more time-consuming we believe the manual consensus gold standard is the most valuable for further research. We also propose a set of annotation classes to be used for similar de-identification tasks.
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| 9. |
- Dalianis, Hercules, et al.
(författare)
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HEALTH BANK - A Workbench for Data Science Applications in Healthcare
- 2015
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Ingår i: Industry Track Workshop. - : CEUR Workshop Proceedings. ; , s. 1-18
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Konferensbidrag (refereegranskat)abstract
- The enormous amounts of data that are generated in the healthcare process and stored in electronic health record (EHR) systems are an underutilized resource that, with the use of data science applica- tions, can be exploited to improve healthcare. To foster the development and use of data science applications in healthcare, there is a fundamen- tal need for access to EHR data, which is typically not readily available to researchers and developers. A relatively rare exception is the large EHR database, the Stockholm EPR Corpus, comprising data from more than two million patients, that has been been made available to a lim- ited group of researchers at Stockholm University. Here, we describe a number of data science applications that have been developed using this database, demonstrating the potential reuse of EHR data to support healthcare and public health activities, as well as facilitate medical re- search. However, in order to realize the full potential of this resource, it needs to be made available to a larger community of researchers, as well as to industry actors. To that end, we envision the provision of an in- frastructure around this database called HEALTH BANK – the Swedish Health Record Research Bank. It will function both as a workbench for the development of data science applications and as a data explo- ration tool, allowing epidemiologists, pharmacologists and other medical researchers to generate and evaluate hypotheses. Aggregated data will be fed into a pipeline for open e-access, while non-aggregated data will be provided to researchers within an ethical permission framework. We believe that HEALTH BANK has the potential to promote a growing industry around the development of data science applications that will ultimately increase the efficiency and effectiveness of healthcare.
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| 10. |
- Dalianis, Hercules, et al.
(författare)
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How Certain are Clinical Assessments? : Annotating Swedish Clinical Text for (Un)certainties, Speculations and Negations
- 2010
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Ingår i: Proceedings of the of the Seventh International Conference on Language Resources and Evaluation, LREC 2010. ; , s. 3071-3075
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Clinical texts contain a large amount of information. Some of this information is embedded in contexts where e.g. a patient status is reasoned about, which may lead to a considerable amount of statements that indicate uncertainty and speculation. We believe that distinguishing such instances from factual statements will be very beneficial for automatic information extraction. We have annotated a subset of the Stockholm Electronic Patient Record Corpus for certain and uncertain expressions as well as speculative and negation keywords, with the purpose of creating a resource for the development of automatic detection of speculative language in Swedish clinical text. We have analyzed the results from the initial annotation trial by means of pairwise Inter-Annotator Agreement (IAA) measured with F-score. Our main findings are that IAA results for certain expressions and negations are very high, but for uncertain expressions and speculative keywords results are less encouraging. These instances need to be defined in more detail. With this annotation trial, we have created an important resource that can be used to further analyze the properties of speculative language in Swedish clinical text. Our intention is to release this subset to other research groups in the future after removing identifiable information.
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