3 citations · 6 across the 5 of their papers we have counts for
9 papers · 1 filter
Automated Identification of Incidentalomas Requiring Follow-Up: A Multi-Anatomy Evaluation of LLM-Based and Supervised Approaches
Namu Park, Farzad Ahmed, Zhaoyi Sun +6
Objective: To evaluate large language models (LLMs) against supervised baselines for fine-grained, lesion-level detection of incidentalomas requiring follow-up, addressing the limi…
Identifying Imaging Follow-Up in Radiology Reports: A Comparative Analysis of Traditional ML and LLM Approaches
Namu Park, Giridhar Kaushik Ramachandran, Kevin Lybarger +4
Large language models (LLMs) have shown considerable promise in clinical natural language processing, yet few domain-specific datasets exist to rigorously evaluate their performanc…
Adapting Biomedical Abstracts into Plain language using Large Language Models
Haritha Gangavarapu, Giridhar Kaushik Ramachandran, Kevin Lybarger +2
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…
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning
Yujuan Velvin Fu, Giridhar Kaushik Ramachandran, Namu Park +4
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 LL…
CACER: Clinical Concept Annotations for Cancer Events and Relations
Yujuan Fu, Giridhar Kaushik Ramachandran, Ahmad Halwani +5
Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationsh…
Extracting Radiological Findings With Normalized Anatomical Information Using a Span-Based BERT Relation Extraction Model
Kevin Lybarger, Aashka Damani, Martin Gunn +2
Medical imaging is critical to the diagnosis and treatment of numerous medical problems, including many forms of cancer. Medical imaging reports distill the findings and observatio…