18 citations · 25 across the 9 of their papers we have counts for
10 papers
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 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…
A Novel Corpus of Annotated Medical Imaging Reports and Information Extraction Results Using BERT-based Language Models
Namu Park, Kevin Lybarger, Giridhar Kaushik Ramachandran +5
Medical imaging is critical to the diagnosis, surveillance, and treatment of many health conditions, including oncological, neurological, cardiovascular, and musculoskeletal disord…
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…
MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions, Experiences and Claims from Social Media using Knowledge-Augmented Pre-trained Language Models
Giridhar Kaushik Ramachandran, Haritha Gangavarapu, Kevin Lybarger +1
In online forums like Reddit, users share their experiences with medical conditions and treatments, including making claims, asking questions, and discussing the effects of treatme…
Extracting Medication Changes in Clinical Narratives using Pre-trained Language Models
Giridhar Kaushik Ramachandran, Kevin Lybarger, Yaya Liu +5
An accurate and detailed account of patient medications, including medication changes within the patient timeline, is essential for healthcare providers to provide appropriate pati…
Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling
Duanshun Li, Jing Liu, Noseong Park +7
0-1 knapsack is of fundamental importance in computer science, business, operations research, etc. In this paper, we present a deep learning technique-based method to solve large-s…