Portability of natural language processing methods to detect suicidality from clinical text in US and UK electronic health records is a research paper published in Journal of Affective Disorders Reports (2022). On theSindex it has a DataRank of 0. It has been cited 23 times.
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National Institutes of Health
Grant: P50MH113838
National Institutes of Health
Grant: R01GM105688
National Institutes of Health
Grant: R01MH105384
National Institutes of Health
Grant: R01MH119177
National Institutes of Health
Grant: R01MH121907
National Institutes of Health
Grant: R01MH121922
King's College London
Grant: RE11682
Medical Research Council
Grant: MR/L017105/1
What are the clinical and educational risk factors for poor academic outcomes in children with Autistic Spectrum Disorder?
National Institute for Health and Care Research
Grant: CS-2018–18-ST2–014
National Institute for Health Research (NIHR)
Grant: CS-2018-18-ST2-014
NIMH NIH HHS
Grant: R41 MH124581
National Institutes of Health
Grant: 5R01GM105688-07
National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms
National Institutes of Health
Grant: 5P50MH113838-04
ALACRITY for Late- and Mid-Life Mood Disorders
National Institutes of Health
Grant: 5R01MH121907-04
Linking VA and non-VA data to study the risk of suicide in chronic pain patients.
National Institutes of Health
Grant: 5R01MH105384-03
Modeling Social Behavior for Healthcare Utilization in Depression
National Institutes of Health
Grant: 5R01MH119177-02
Predicting Self-Harm, Suicide Attempt, and Suicidal Death using Longitudinal EHR, Claims and Mortality Data
National Institutes of Health
Grant: 5R01MH121922-02
4/4: Leveraging EHR-linked biobanks for deep phenotyping, polygenic risk score modeling, and outcomes analysis in psychiatric disorders
Academy of Medical Sciences
The Psychiatry Research Trust
Greater Rochester Health Foundation
South London and Maudsley NHS Foundation Trust
FWCI
4.13
Citation Percentile
0.9%
Citation Trend
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