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View article: Prompting Large Language Models to Detect Dementia Family Caregivers
Prompting Large Language Models to Detect Dementia Family Caregivers Open
Social media, such as Twitter, provides opportunities for caregivers of dementia patients to share their experiences and seek support for a variety of reasons. Availability of this information online also paves the way for the development …
View article: Spurious Correlations and Beyond: Understanding and Mitigating Shortcut Learning in SDOH Extraction with Large Language Models
Spurious Correlations and Beyond: Understanding and Mitigating Shortcut Learning in SDOH Extraction with Large Language Models Open
Social determinants of health (SDOH) extraction from clinical text is critical for downstream healthcare analytics. Although large language models (LLMs) have shown promise, they may rely on superficial cues leading to spurious predictions…
View article: Adapting Biomedical Abstracts into Plain language using Large Language Models
Adapting Biomedical Abstracts into Plain language using Large Language Models Open
A vast amount of medical knowledge is available for public use through online health forums, and question-answering platforms on social media. The majority of the population in the United States doesn't have the right amount of health lite…
View article: BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning.
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning. Open
Large language models (LLMs) such as ChatGPT are fine-tuned on large and diverse instruction-following corpora, and can generalize to new tasks. However, those instruction-tuned LLMs often perform poorly in specialized medical natural lang…
View article: Does Data Contamination Detection Work (Well) for LLMs? A Survey and Evaluation on Detection Assumptions
Does Data Contamination Detection Work (Well) for LLMs? A Survey and Evaluation on Detection Assumptions Open
Large language models (LLMs) have demonstrated great performance across various benchmarks, showing potential as general-purpose task solvers. However, as LLMs are typically trained on vast amounts of data, a significant concern in their e…
View article: CACER: Clinical concept Annotations for Cancer Events and Relations
CACER: Clinical concept Annotations for Cancer Events and Relations Open
Objective Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symp…
View article: Collaborative Design for Job-Seekers with Autism: A Conceptual Framework for Future Research
Collaborative Design for Job-Seekers with Autism: A Conceptual Framework for Future Research Open
The success of employment is highly related to a job seeker's capability of communicating and collaborating with others. While leveraging one's network during the job-seeking process is intuitive to the neurotypical, this can be challengin…
View article: Large language models for biomedicine: foundations, opportunities, challenges, and best practices
Large language models for biomedicine: foundations, opportunities, challenges, and best practices Open
Objectives Generative large language models (LLMs) are a subset of transformers-based neural network architecture models. LLMs have successfully leveraged a combination of an increased number of parameters, improvements in computational ef…
View article: Extracting Social Determinants of Health from Pediatric Patient Notes Using Large Language Models: Novel Corpus and Methods
Extracting Social Determinants of Health from Pediatric Patient Notes Using Large Language Models: Novel Corpus and Methods Open
Social determinants of health (SDoH) play a critical role in shaping health outcomes, particularly in pediatric populations where interventions can have long-term implications. SDoH are frequently studied in the Electronic Health Record (E…
View article: A Novel Corpus of Annotated Medical Imaging Reports and Information Extraction Results Using BERT-based Language Models
A Novel Corpus of Annotated Medical Imaging Reports and Information Extraction Results Using BERT-based Language Models Open
Medical imaging is critical to the diagnosis, surveillance, and treatment of many health conditions, including oncological, neurological, cardiovascular, and musculoskeletal disorders, among others. Radiologists interpret these complex, un…
View article: MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection
MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection Open
This paper presents the MasonTigers entry to the SemEval-2024 Task 8 - Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection. The task encompasses Binary Human-Written vs. Machine-Generated Text Classific…
View article: MASON-NLP at eRisk 2023: Deep Learning-Based Detection of Depression Symptoms from Social Media Texts
MASON-NLP at eRisk 2023: Deep Learning-Based Detection of Depression Symptoms from Social Media Texts Open
Depression is a mental health disorder that has a profound impact on people's lives. Recent research suggests that signs of depression can be detected in the way individuals communicate, both through spoken words and written texts. In part…
View article: LeafAI: query generator for clinical cohort discovery rivaling a human programmer
LeafAI: query generator for clinical cohort discovery rivaling a human programmer Open
Objective Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive technical and biomedical expertise. We sought to create a system c…
View article: Prompt-based Extraction of Social Determinants of Health Using Few-shot Learning
Prompt-based Extraction of Social Determinants of Health Using Few-shot Learning Open
Social determinants of health (SDOH) documented in the electronic health record through unstructured text are increasingly being studied to understand how SDOH impacts patient health outcomes. In this work, we utilize the Social History An…
View article: MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions, Experiences and Claims from Social Media using Knowledge-Augmented Pre-trained Language Models
MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions, Experiences and Claims from Social Media using Knowledge-Augmented Pre-trained Language Models Open
In online forums like Reddit, users share their experiences with medical conditions and treatments, including making claims, asking questions, and discussing the effects of treatments on their health. Building systems to understand this in…
View article: LeafAI: query generator for clinical cohort discovery rivaling a human programmer
LeafAI: query generator for clinical cohort discovery rivaling a human programmer Open
Objective: Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive technical and biomedical expertise. We sought to create a system …
View article: Leveraging natural language processing to augment structured social determinants of health data in the electronic health record
Leveraging natural language processing to augment structured social determinants of health data in the electronic health record Open
Objective Social determinants of health (SDOH) impact health outcomes and are documented in the electronic health record (EHR) through structured data and unstructured clinical notes. However, clinical notes often contain more comprehensiv…
View article: Progress Note Understanding -- Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task
Progress Note Understanding -- Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task Open
Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designed to document all the care provided to patients, but it als…
View article: The 2022 n2c2/UW shared task on extracting social determinants of health
The 2022 n2c2/UW shared task on extracting social determinants of health Open
Objective The n2c2/UW SDOH Challenge explores the extraction of social determinant of health (SDOH) information from clinical notes. The objectives include the advancement of natural language processing (NLP) information extraction techniq…
View article: Advancements in extracting social determinants of health information from narrative text
Advancements in extracting social determinants of health information from narrative text Open
Journal Article Advancements in extracting social determinants of health information from narrative text Get access Kevin Lybarger, Kevin Lybarger Department of Information Sciences and Technology, George Mason University, Fairfax, Virgini…
View article: The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Health
The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Health Open
Objective: The n2c2/UW SDOH Challenge explores the extraction of social determinant of health (SDOH) information from clinical notes. The objectives include the advancement of natural language processing (NLP) information extraction techni…