13 citations · 28 across the 10 of their papers we have counts for
11 papers
Misaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models
Star S. D. Liu, Xiyu Ding, Robert B. Barrett +3
How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood. We investigated how four open-weight LLMs (Qwen-2.5-7B/32B and Llama…
Large Language Model-Based Agents for Automated Research Reproducibility: An Exploratory Study in Alzheimer's Disease
Nic Dobbins, Christelle Xiong, Kristine Lan +1
Objective: To demonstrate the capabilities of Large Language Models (LLMs) as autonomous agents to reproduce findings of published research studies using the same or similar datase…
Generalizable and Scalable Multistage Biomedical Concept Normalization Leveraging Large Language Models
Nicholas J Dobbins
Background: Biomedical entity normalization is critical to biomedical research because the richness of free-text clinical data, such as progress notes, can often be fully leveraged…
Extracting Social Determinants of Health from Pediatric Patient Notes Using Large Language Models: Novel Corpus and Methods
Yujuan Fu, Giridhar Kaushik Ramachandran, Nicholas J Dobbins +7
Social determinants of health (SDoH) play a critical role in shaping health outcomes, particularly in pediatric populations where interventions can have long-term implications. SDo…
Prompt-based Extraction of Social Determinants of Health Using Few-shot Learning
Giridhar Kaushik Ramachandran, Yujuan Fu, Bin Han +4
Social determinants of health (SDOH) documented in the electronic health record through unstructured text are increasingly being studied to understand how SDOH impacts patient heal…
LeafAI: query generator for clinical cohort discovery rivaling a human programmer
Nicholas J Dobbins, Bin Han, Weipeng Zhou +5
Objective: Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive techni…
Leveraging Natural Language Processing to Augment Structured Social Determinants of Health Data in the Electronic Health Record
Kevin Lybarger, Nicholas J Dobbins, Ritche Long +4
Objective: Social determinants of health (SDOH) impact health outcomes and are documented in the electronic health record (EHR) through structured data and unstructured clinical no…
The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteria
Nicholas J Dobbins, Tony Mullen, Ozlem Uzuner +1
Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criter…
The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP models
Yao Yan, Thomas Yu, Kathleen Muenzen +14
Objective The evaluation of natural language processing (NLP) models for clinical text de-identification relies on the availability of clinical notes, which is often restricted due…
Performance of Automatic De-identification Across Different Note Types
Nicholas Dobbins, David Wayne, Kahyun Lee +2
Free-text clinical notes detail all aspects of patient care and have great potential to facilitate quality improvement and assurance initiatives as well as advance clinical researc…
Transferability of Neural Network Clinical De-identification Systems
Kahyun Lee, Nicholas J. Dobbins, Bridget McInnes +2
Objective: Neural network de-identification studies have focused on individual datasets. These studies assume the availability of a sufficient amount of human-annotated data to tra…