| 1. |
- Allvin, H., et al.
(författare)
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Characteristics and Analysis of Finnish and Swedish Clinical Intensive Care Nursing Narratives
- 2010
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Ingår i: Proceedings of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents. ; , s. 53-60
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Konferensbidrag (refereegranskat)abstract
- We present a comparative study of Finnish and Swedish free-text nursing narratives from intensive care. Although the two languages are linguistically very dissimilar, our hypothesis is that there are similarities that are important and interesting from a language technology point of view. This may have implications when building tools to support producing and using health care documentation. We perform a comparative qualitative analysis based on structure and content, as well as a comparative quantitative analysis on Finnish and Swedish Intensive Care Unit (ICU) nursing narratives. Our findings are that ICU nursing narratives in Finland and Sweden have many properties in common, but that many of these are challenging when it comes to developing language technology tools.
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| 2. |
- Velupillai, Sumithra, et al.
(författare)
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Identifying suicidal adolescents from mental health records using natural language processing
- 2019
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Ingår i: 17th World Congress on Medical and Health Informatics, MEDINFO 2019. - : IOS Press. - 9781643680026 ; , s. 413-417
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Konferensbidrag (refereegranskat)abstract
- Suicidal ideation is a risk factor for self-harm, completed suicide and can be indicative of mental health issues. Adolescents are a particularly vulnerable group, but few studies have examined suicidal behaviour prevalence in large cohorts. Electronic Health Records (EHRs) are a rich source of secondary health care data that could be used to estimate prevalence. Most EHR documentation related to suicide risk is written in free text, thus requiring Natural Language Processing (NLP) approaches. We adapted and evaluated a simple lexicon- and rule-based NLP approach to identify suicidal adolescents from a large EHR database. We developed a comprehensive manually annotated EHR reference standard and assessed NLP performance at both document and patient level on data from 200 patients (~5000 documents). We achieved promising results (>80% f1 score at both document and patient level). Simple NLP approaches can be successfully used to identify patients who exhibit suicidal risk behaviour, and our proposed approach could be useful for other populations and settings.
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| 3. |
- Viani, N., et al.
(författare)
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Annotating temporal relations to determine the onset of psychosis symptoms
- 2019
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Ingår i: 17th World Congress on Medical and Health Informatics, MEDINFO 2019. - : IOS Press. - 9781643680026 ; , s. 418-422
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Konferensbidrag (refereegranskat)abstract
- For patients with a diagnosis of schizophrenia, determining symptom onset is crucial for timely and successful intervention. In mental health records, information about early symptoms is often documented only in free text, and thus needs to be extracted to support clinical research. To achieve this, natural language processing (NLP) methods can be used. Development and evaluation of NLP systems requires manually annotated corpora. We present a corpus of mental health records annotated with temporal relations for psychosis symptoms. We propose a methodology for document selection and manual annotation to detect symptom onset information, and develop an annotated corpus. To assess the utility of the created corpus, we propose a pilot NLP system. To the best of our knowledge, this is the first temporally-annotated corpus tailored to a specific clinical use-case.
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