186 citations · 334 across the 20 of their papers we have counts for
6 papers · 1 filter
From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence
David Oniani, Jordan Hilsman, Yifan Peng +5
In 2020, the U.S. Department of Defense officially disclosed a set of ethical principles to guide the use of Artificial Intelligence (AI) technologies on future battlefields. Despi…
Large Language Models Vote: Prompting for Rare Disease Identification
David Oniani, Jordan Hilsman, Hang Dong +3
The emergence of generative Large Language Models (LLMs) emphasizes the need for accurate and efficient prompting approaches. LLMs are often applied in Few-Shot Learning (FSL) cont…
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…
Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses
Liyan Tang, Yifan Peng, Yanshan Wang +3
A human decision-maker benefits the most from an AI assistant that corrects for their biases. For problems such as generating interpretation of a radiology report given findings, a…
ReDWINE: A Clinical Datamart with Text Analytical Capabilities to Facilitate Rehabilitation Research
David Oniani, Bambang Parmanto, Andi Saptono +9
Rehabilitation research focuses on determining the components of a treatment intervention, the mechanism of how these components lead to recovery and rehabilitation, and ultimately…
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…