106 citations · 125 across the 11 of their papers we have counts for
13 papers
Deep learning for autism detection using clinical notes: A comparison of transfer learning for a transparent and black-box approach
Gondy Leroy, Prakash Bisht, Sai Madhuri Kandula +2
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose rising prevalence places increasing demands on a lengthy diagnostic process. Machine learning (ML) ha…
Comparative Evaluation of Text and Audio Simplification: A Methodological Replication Study
Prosanta Barai, Gondy Leroy, Arif Ahmed
This study serves as a methodological replication of Leroy et al. (2022) research, which investigated the impact of text simplification on healthcare information comprehension in t…
Automated Feedback Loops to Protect Text Simplification with Generative AI from Information Loss
Abhay Kumara Sri Krishna Nandiraju, Gondy Leroy, David Kauchak +1
Understanding health information is essential in achieving and maintaining a healthy life. We focus on simplifying health information for better understanding. With the availabilit…
Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluation
Yue Guo, Jae Ho Sohn, Gondy Leroy +1
Plain language summaries (PLSs) are essential for facilitating effective communication between clinicians and patients by making complex medical information easier for laypeople to…
ICD Codes are Insufficient to Create Datasets for Machine Learning: An Evaluation Using All of Us Data for Coccidioidomycosis and Myocardial Infarction
Abigail E. Whitlock, Gondy Leroy, Fariba M. Donovan +1
In medicine, machine learning (ML) datasets are often built using the International Classification of Diseases (ICD) codes. As new models are being developed, there is a need for l…
Role of Dependency Distance in Text Simplification: A Human vs ChatGPT Simplification Comparison
Sumi Lee, Gondy Leroy, David Kauchak +1
This study investigates human and ChatGPT text simplification and its relationship to dependency distance. A set of 220 sentences, with increasing grammatical difficulty as measure…
Crowdsourcing with Enhanced Data Quality Assurance: An Efficient Approach to Mitigate Resource Scarcity Challenges in Training Large Language Models for Healthcare
P. Barai, G. Leroy, P. Bisht +5
Large Language Models (LLMs) have demonstrated immense potential in artificial intelligence across various domains, including healthcare. However, their efficacy is hindered by the…
Utilizing Large Language Models to Generate Synthetic Data to Increase the Performance of BERT-Based Neural Networks
Chancellor R. Woolsey, Prakash Bisht, Joshua Rothman +1
An important issue impacting healthcare is a lack of available experts. Machine learning (ML) models could resolve this by aiding in diagnosing patients. However, creating datasets…
Text and Audio Simplification: Human vs. ChatGPT
Gondy Leroy, David Kauchak, Philip Harber +2
Text and audio simplification to increase information comprehension are important in healthcare. With the introduction of ChatGPT, an evaluation of its simplification performance i…
Effects of Added Emphasis and Pause in Audio Delivery of Health Information
Arif Ahmed, Gondy Leroy, Stephen A. Rains +3
Health literacy is crucial to supporting good health and is a major national goal. Audio delivery of information is becoming more popular for informing oneself. In this study, we e…
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
Yue Guo, Tal August, Gondy Leroy +2
While there has been significant development of models for Plain Language Summarization (PLS), evaluation remains a challenge. PLS lacks a dedicated assessment metric, and the suit…
Retrieval augmentation of large language models for lay language generation
Yue Guo, Wei Qiu, Gondy Leroy +2
Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility. However, the applicability of these m…
AutoMeTS: The Autocomplete for Medical Text Simplification
Hoang Van, David Kauchak, Gondy Leroy
The goal of text simplification (TS) is to transform difficult text into a version that is easier to understand and more broadly accessible to a wide variety of readers. In some do…