22 Result(s)
within
Sumithra Velupillai
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Article
Open AccessAutism spectrum disorders as a risk factor for adolescent self-harm: a retrospective cohort study of 113,286 young people in the UK
Individuals with autism spectrum disorder (ASD) are at particularly high risk of suicide and suicide attempts. Presentation to a hospital with self-harm is one of the strongest risk factors for later suicide. ...
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Article
Open AccessTemporal and diurnal variation in social media posts to a suicide support forum
Rates of suicide attempts and deaths are highest on Mondays and these occur more frequently in the morning or early afternoon, suggesting weekly temporal and diurnal variation in suicidal behaviour. It is unkn...
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Article
Open AccessA natural language processing approach for identifying temporal disease onset information from mental healthcare text
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variabl...
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Chapter and Conference Paper
Linguistic Uncertainty in Clinical NLP: A Taxonomy, Dataset and Approach
Linguistic uncertainty is prevalent in electronic health records (EHRs). The ability to handle and preserve uncertainty in natural language is an essential skill for clinicians, facilitating decidability and e...
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Article
Open AccessApplied natural language processing in mental health big data
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Chapter
Big Data: Knowledge Discovery and Data Repositories
“Big Data” is a concept that has been used in the last 10–15 years to describe the increasing complexity and amount of data available at scale in organizations and companies—data that often requires novel comp...
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Article
Open AccessGeneration and evaluation of artificial mental health records for Natural Language Processing
A serious obstacle to the development of Natural Language Processing (NLP) methods in the clinical domain is the accessibility of textual data. The mental health domain is particularly challenging, partly beca...
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Article
Open AccessTemporal information extraction from mental health records to identify duration of untreated psychosis
Duration of untreated psychosis (DUP) is an important clinical construct in the field of mental health, as longer DUP can be associated with worse intervention outcomes. DUP estimation requires knowledge about wh...
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Chapter and Conference Paper
Generating Positive Psychosis Symptom Keywords from Electronic Health Records
The development of Natural Language Processing (NLP) solutions for ...
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Article
Open AccessIdentifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing
Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic H...
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Article
Open AccessClinical Natural Language Processing in languages other than English: opportunities and challenges
Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) f...
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Article
Open AccessCorrection: Corrigendum: Characterisation of mental health conditions in social media using Informed Deep Learning
Scientific Reports 7: Article number: 45141; published online: 22 March 2017; updated: 16 May 2017 One of the Supplementary Information files that accompany this study was inadvertently omitted in the original...
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Article
Open AccessCharacterisation of mental health conditions in social media using Informed Deep Learning
The number of people affected by mental illness is on the increase and with it the burden on health and social care use, as well as the loss of both productivity and quality-adjusted life-years. Natural langua...
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Article
Open AccessNormalizing acronyms and abbreviations to aid patient understanding of clinical texts: ShARe/CLEF eHealth Challenge 2013, Task 2
The ShARe/CLEF eHealth challenge lab aims to stimulate development of natural language processing and information retrieval technologies to aid patients in understanding their clinical reports. In clinical tex...
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Article
Open AccessLouhi 2014: Special issue on health text mining and information analysis
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Chapter and Conference Paper
SCAN: A Swedish Clinical Abbreviation Normalizer
Abbreviations pose a challenge for information extraction systems. In clinical text, abbreviations are abundant, as this type of documentation is written under time-pressure. We report work on characterizing a...
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Chapter and Conference Paper
Overview of the ShARe/CLEF eHealth Evaluation Lab 2014
This paper reports on the 2nd ShARe/CLEFeHealth evaluation lab which continues our evaluation resource building activities for the medical domain. In this lab we focus on patients’ information needs as opposed...
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Chapter and Conference Paper
Overview of the ShARe/CLEF eHealth Evaluation Lab 2013
Discharge summaries and other free-text reports in healthcare transfer information between working shifts and geographic locations. Patients are likely to have difficulties in understanding their content, beca...
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Chapter and Conference Paper
Fine-Grained Certainty Level Annotations Used for Coarser-Grained E-Health Scenarios
An important task in information access methods is distinguishing factual information from speculative or negated information. Fine-grained certainty levels of diagnostic statements in Swedish clinical text ar...
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Article
Open AccessLouhi 2010: Special issue on Text and Data Mining of Health Documents
The papers presented in this supplement focus and reflect on computer use in every-day clinical work in hospitals and clinics such as electronic health record systems, pre-processing for computer aided summari...
