34 citations · 47 across the 14 of their papers we have counts for
14 papers
A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework
Chenyu Li, Zohaib Akhtar, Mingu Kwak +13
As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which uses LLMs to evaluate model o…
Generative Foundation Model for Structured and Unstructured Electronic Health Records
Sonish Sivarajkumar, Hang Zhang, Yuelyu Ji +6
Electronic health records (EHRs) are rich clinical data sources but complex repositories of patient data, spanning structured elements (demographics, vitals, lab results, codes), u…
Automating Adjudication of Cardiovascular Events Using Large Language Models
Sonish Sivarajkumar, Kimia Ameri, Chuqin Li +2
Cardiovascular events, such as heart attacks and strokes, remain a leading cause of mortality globally, necessitating meticulous monitoring and adjudication in clinical trials. Thi…
Mitigating the Risk of Health Inequity Exacerbated by Large Language Models
Yuelyu Ji, Wenhe Ma, Sonish Sivarajkumar +6
Recent advancements in large language models have demonstrated their potential in numerous medical applications, particularly in automating clinical trial matching for translationa…
RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Texts
Yuelyu Ji, Zhuochun Li, Rui Meng +7
This paper introduces the RAG-RLRC-LaySum framework, designed to make complex biomedical research understandable to laymen through advanced Natural Language Processing (NLP) techni…
Precision Rehabilitation for Patients Post-Stroke based on Electronic Health Records and Machine Learning
Fengyi Gao, Xingyu Zhang, Sonish Sivarajkumar +7
In this study, we utilized statistical analysis and machine learning methods to examine whether rehabilitation exercises can improve patients post-stroke functional abilities, as w…
A Framework for Human Evaluation of Large Language Models in Healthcare Derived from Literature Review
Thomas Yu Chow Tam, Sonish Sivarajkumar, Sumit Kapoor +12
With generative artificial intelligence (AI), particularly large language models (LLMs), continuing to make inroads in healthcare, it is critical to supplement traditional automate…
Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning
Sonish Sivarajkumar, Pratyush Tandale, Ankit Bhardwaj +6
Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine lea…
An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing
Sonish Sivarajkumar, Mark Kelley, Alyssa Samolyk-Mazzanti +2
Large language models (LLMs) have shown remarkable capabilities in Natural Language Processing (NLP), especially in domains where labeled data is scarce or expensive, such as clini…
Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records
Sonish Sivarajkumar, Yufei Huang, Yanshan Wang
Objective: To pre-train fair and unbiased patient representations from Electronic Health Records (EHRs) using a novel weighted loss function that reduces bias and improves fairness…
Mining Clinical Notes for Physical Rehabilitation Exercise Information: Natural Language Processing Algorithm Development and Validation Study
Sonish Sivarajkumar, Fengyi Gao, Parker E. Denny +4
Post-stroke patient rehabilitation requires precise, personalized treatment plans. Natural Language Processing (NLP) offers potential to extract valuable exercise information from…
Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks
David Oniani, Sonish Sivarajkumar, Yanshan Wang
Clinical Natural Language Processing (NLP) has become an emerging technology in healthcare that leverages a large amount of free-text data in electronic health records (EHRs) to im…
Extraction of Sleep Information from Clinical Notes of Patients with Alzheimer's Disease Using Natural Language Processing
Sonish Sivarajkumar, Thomas Yu CHow Tam, Haneef Ahamed Mohammad +4
Alzheimer's Disease (AD) is the most common form of dementia in the United States. Sleep is one of the lifestyle-related factors that has been shown critical for optimal cognitive…
HealthPrompt: A Zero-shot Learning Paradigm for Clinical Natural Language Processing
Sonish Sivarajkumar, Yanshan Wang
Deep learning algorithms are dependent on the availability of large-scale annotated clinical text datasets. The lack of such publicly available datasets is the biggest bottleneck f…