52 citations · 73 across the 12 of their papers we have counts for
12 papers
Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications
David Oniani, Jordan Hilsman, Chengxi Zang +4
A drug molecule is a substance that changes the organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for tre…
Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines
David Oniani, Xizhi Wu, Shyam Visweswaran +4
Background Large Language Models (LLMs), enhanced with Clinical Practice Guidelines (CPGs), can significantly improve Clinical Decision Support (CDS). However, methods for incorpor…
In-Context Learning Functions with Varying Number of Minima
David Oniani, Yanshan Wang
Large Language Models (LLMs) have proven effective at In-Context Learning (ICL), an ability that allows them to create predictors from labeled examples. Few studies have explored t…
Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI
Mahyar Abbasian, Elahe Khatibi, Iman Azimi +11
Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process.…
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…
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…
Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models
David Oniani, Sreekanth Sreekumar, Renuk DeAlmeida +6
Health literacy is the central focus of Healthy People 2030, the fifth iteration of the U.S. national goals and objectives. People with low health literacy usually have trouble und…
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…
Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review
Anusha Bompelli, Yanshan Wang, Ruyuan Wan +8
Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health recor…
A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19
David Oniani, Yanshan Wang
COVID-19 has resulted in an ongoing pandemic and as of 12 June 2020, has caused more than 7.4 million cases and over 418,000 deaths. The highly dynamic and rapidly evolving situati…