ArticleData in brief2019
The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications.
Article in Data in brief, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 44 citations in OpenAlex.
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- BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- A Comprehensive Evaluation of Biomedical Entity Linking Models.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2023Article
- An analysis of entity normalization evaluation biases in specialized domains.BMC bioinformatics · 2023Article
- Revealing the immune cell subtype reconstitution profile in patients from the CLARITY study using deconvolution algorithms after cladribine tablets treatment.Scientific reports · 2023Article
- A risk identification model for detection of patients at risk of antidepressant discontinuation.Frontiers in artificial intelligence · 2023Article
- An overview of biomedical entity linking throughout the years.Journal of biomedical informatics · 2023Review
- An Assessment of Mentions of Adverse Drug Events on Social Media With Natural Language Processing: Model Development and Analysis.JMIR medical informatics · 2022Article
- Automated gathering of real-world data from online patient forums can complement pharmacovigilance for rare cancers.Scientific reports · 2022Article
- A systematic approach for developing a corpus of patient reported adverse drug events: A case study for SSRI and SNRI medications.Journal of biomedical informatics · 2019Article
- Home Healthcare Clinical Notes Predict Patient Hospitalization and Emergency Department Visits.Nursing researchArticle
Corrections and comments
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Authors and funding
15 authors at 9 institutions in 1 country.
Funding
Abstract
The "Psychiatric Treatment Adverse Reactions" (PsyTAR) dataset contains patients' expression of effectiveness and adverse drug events associated with psychiatric medications. The PsyTAR was generated in four phases. In the first phase, a sample of 891 drugs reviews posted by patients on an online healthcare forum, "askapatient.com", was collected for four psychiatric drugs: Zoloft, Lexapro, Cymbalta, and Effexor XR. For each drug review, patient demographic information, duration of treatment, and satisfaction with the drugs were reported. In the second phase, sentence classification, drug reviews were split to 6009 sentences, and each sentence was labeled for the presence of Adverse Drug Reaction (ADR), Withdrawal Symptoms (WDs), Sign/Symptoms/Illness (SSIs), Drug Indications (DIs), Drug Effectiveness (EF), Drug Infectiveness (INF), and Others (not applicable). In the third phases, entities including ADRs (4813 mentions), WDs (590 mentions), SSIs (1219 mentions), and DIs (792 mentions) were identified and extracted from the sentences. In the four phases, all the identified entities were mapped to the corresponding UMLS Metathesaurus concepts (916) and SNOMED CT concepts (755). In this phase, qualifiers representing severity and persistency of ADRs, WDs, SSIs, and DIs (e.g., mild, short term) were identified. All sentences and identified entities were linked to the original post using IDs (e.g., Zoloft.1, Effexor.29, Cymbalta.31). The PsyTAR dataset can be accessed via Online Supplement #1 under the CC BY 4.0 Data license. The updated versions of the dataset would also be accessible in https://sites.google.com/view/pharmacovigilanceinpsychiatry/home.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.