David Oniani

According to our database, David Oniani authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications.

David Oniani, Jordan Hilsman, Chengxi Zang, Junmei Wang, Lianjin Cai, Jan Zawala, Yanshan Wang

CoRR, 2024

Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines.

David Oniani, Xizhi Wu, Shyam Visweswaran, Sumit Kapoor, Shravan Kooragayalu, Katelyn Polanska, Yanshan Wang

CoRR, 2024

2023

ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research.

David Oniani, Bambang Parmanto, Andi Saptono, Allyn Bove, Janet Freburger, Shyam Visweswaran, Nickie Cappella, Brian McLay, Jonathan C. Silverstein, Michael J. Becich, Anthony Delitto, Elizabeth Skidmore, Yanshan Wang

Int. J. Medical Informatics, September, 2023

Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare.

David Oniani, Jordan Hilsman, Yifan Peng, Ronald K. Poropatich, Jeremy C. Pamplin, Gary L. Legault, Yanshan Wang

npj Digit. Medicine, 2023

In-Context Learning Functions with Varying Number of Minima.

David Oniani, Yanshan Wang

CoRR, 2023

Foundation Metrics: Quantifying Effectiveness of Healthcare Conversations powered by Generative AI.

Mahyar Abbasian, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh C. Jain, Amir M. Rahmani

CoRR, 2023

Large Language Models Vote: Prompting for Rare Disease Identification.

David Oniani, Jordan Hilsman, Hang Dong, Fengyi Gao, Shiven Verma, Yanshan Wang

CoRR, 2023

From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence.

David Oniani, Jordan Hilsman, Yifan Peng, Ronald K. Poropatich, Jeremy C. Pamplin, Gary L. Legault, Yanshan Wang

CoRR, 2023

2022

Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models.

David Oniani, Sreekanth Sreekumar, Renuk DeAlmeida, Dinuk DeAlmeida, Vivian Hui, Young Ji Lee, Yiye Zhang, Leming Zhou, Yanshan Wang

CoRR, 2022

Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks.

David Oniani, Sonish Sivarajkumar, Yanshan Wang

CoRR, 2022

Extraction of Sleep Information from Clinical Notes of Alzheimer's Disease Patients Using Natural Language Processing.

Haneef Ahamed Mohammad, Sonish Sivarajkumar, Samual Viggiano, David Oniani, Shyam Visweswaran, Yanshan Wang

CoRR, 2022

2021

Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping.

David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen

CoRR, 2021

Social determinants of health in the era of artificial intelligence with electronic health records: A systematic review.

Anusha Bompelli, Yanshan Wang, Ruyuan Wan, Esha Singh, Yuqi Zhou, Lin Xu, David Oniani, Bhavani Singh Agnikula Kshatriya, Joyce E. Balls-Berry, Rui Zhang

CoRR, 2021

Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features.

David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen

CoRR, 2021

2020

Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases.

David Oniani, Guoqian Jiang, Hongfang Liu, Feichen Shen

J. Am. Medical Informatics Assoc., 2020

A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19.

David Oniani, Yanshan Wang

Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020