JaMor Hairston
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View article: Characterization of Reddit Posts About Xylazine-Associated Wounds: Qualitative Study
Characterization of Reddit Posts About Xylazine-Associated Wounds: Qualitative Study Open
Background Xylazine has been associated with skin wounds. The rising prevalence of xylazine and its debated role in wound causation have sparked concerns among public health professionals, medical experts, and people who use drugs. Objecti…
View article: Automating inductive thematic analyses of health content using large language models: a proof-of-concept study using social media data
Automating inductive thematic analyses of health content using large language models: a proof-of-concept study using social media data Open
Objectives Large language models (LLMs) face challenges in inductive thematic analysis, a task requiring deep interpretive, domain-specific expertise. We evaluated the feasibility of using LLMs to replicate expert-driven thematic analysis …
View article: Automated Thematic Analyses Using LLMs: Xylazine Wound Management Social Media Chatter Use Case
Automated Thematic Analyses Using LLMs: Xylazine Wound Management Social Media Chatter Use Case Open
Background Large language models (LLMs) face challenges in inductive thematic analysis, a task requiring deep interpretive and domain-specific expertise. We evaluated the feasibility of using LLMs to replicate expert-driven thematic analys…
View article: Data science and artificial intelligence in biology, health, and healthcare
Data science and artificial intelligence in biology, health, and healthcare Open
View article: Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study
Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study Open
Background The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However,…
View article: Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection
Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection Open
View article: Transfer Learning for the Prediction of Entity Modifiers in Clinical Text: Application to Opioid Use Disorder Case Detection
Transfer Learning for the Prediction of Entity Modifiers in Clinical Text: Application to Opioid Use Disorder Case Detection Open
Background: The semantics of entities extracted from a clinical text can be dramatically altered by modifiers, including entity negation, uncertainty, conditionality, severity, and subject. Existing models for determining modifiers of clin…
View article: Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text
Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text Open
Natural Language Processing can be used to identify opioid use disorder in patients from clinical text1. We annotate a corpus of clinical text for mentions of concepts associated with unhealthy use of opiates including concept modifiers su…