Challenge: Current research indicates patients are often unaware of such critical information / advice related to their prescription drugs due to lack of communication with their doctors and/or pharmacists.
Approach: They propose an annotation scheme for annotating safety critical advice from drug usage guidelines and an annotated dataset containing drug usage guideline data.
Outcome: The proposed dataset will accelerate further release of annotated drug usage guideline datasets and research on automatically filtering safety critical information from these documents.

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Annotation of Adverse Drug Reactions in Patients’ Weblogs (2020.lrec-1)

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Challenge: Adverse drug reactions are a severe problem that significantly degrade quality of life and make the therapeutic approach unacceptable.
Approach: They crawled patient’s weblog articles shared on an online patient-networking platform and annotated the effects of drugs therein reported.
Outcome: The proposed dataset is unique for the richness of annotated information, including detailed descriptions of drug reactions with full context.
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages (2024.lrec-main)

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Challenge: Existing clinical corpora mostly revolves around scientific articles in English . existing literature is limited to only a few scientific articles .
Approach: They propose to use user-generated data sources to uncover adverse drug reactions . existing clinical corpora mostly revolves around scientific articles in english . authors provide statistics to highlight certain challenges associated with the corpus .
Outcome: The proposed corpus includes 12 entity types, four attribute types, and 13 relation types . it provides strong baselines for extracting entities and relations between entities .
DrugWatch: A Comprehensive Multi-Source Data Visualisation Platform for Drug Safety Information (2024.acl-demos)

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Challenge: Drug safety research is crucial for maintaining public health, but resources available to the public are limited.
Approach: They propose an easy-to-use and interactive multi-source information visualisation platform for drug safety study.
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Conceptualisation and Annotation of Drug Nonadherence Information for Knowledge Extraction from Patient-Generated Texts (D19-55)

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Challenge: a new approach to knowledge extraction (KE) is needed for the health domain.
Approach: They propose an approach to extracting knowledge about antidepressant drug nonadherence from health forums.
Outcome: The proposed approach can be used to extract knowledge about antidepressant drug nonadherence from health forums.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective (2022.lrec-1)

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Challenge: a recent study shows that the class labels of german documents containing ADRs are imbalanced . clinical trials and physicians prescribing medications cannot cover every potential use case.
Approach: They propose to use binary annotated documents from a german patient forum to detect ADRs.
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Development of a Corpus Annotated with Medications and their Attributes in Psychiatric Health Records (2020.lrec-1)

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Challenge: Free text fields within electronic health records (EHRs) contain valuable clinical information which is often missed when conducting research using EHR databases.
Approach: They propose to extract medication annotations from mental health records by including contextual information around them.
Outcome: The aim of the study is to provide a more complete picture behind the mention of medications in the health records, by including additional contextual information around them.
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text (2022.emnlp-main)

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Challenge: Using NLP methods to discover and extract adverse drug events from unstructured textual data is difficult because it requires time-consuming manual curation.
Approach: They propose to use a hierarchical event schema to extract annotated events from medical case reports and biomedical literature to analyze patient data.
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Identifying Self-Disclosures of Use, Misuse and Addiction in Community-based Social Media Posts (2024.findings-naacl)

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Challenge: Experimental results show that identifying the phases of opioid use disorder is highly contextual and challenging.
Approach: They analyze 2500 opioid-related posts from various subreddits labeled with six different phases of opioid use . they annotate span-level extractive explanations and critically evaluate state-of-the-art models in a supervised, few-shot, or zero-shot setting.
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Towards a Versatile Medical-Annotation Guideline Feasible Without Heavy Medical Knowledge: Starting From Critical Lung Diseases (2020.lrec-1)

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Challenge: Current annotation policies for medical corpora are not standardized across clinical texts of different types.
Approach: They propose to annotate medical records of various types using a named entity recognition (NER) task.
Outcome: The proposed annotation scheme is applicable to large-scale clinical NLP projects.
A Dataset for N-ary Relation Extraction of Drug Combinations (2022.naacl-main)

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Challenge: Combination therapies are becoming standard of care for diseases such as cancer, tuberculosis, malaria and HIV.
Approach: They construct an expert-annotated dataset for extracting drug combinations from the scientific literature.
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