Minnesota Department of Health

Large language models for disease diagnosis: a scoping review

Shuang Zhou, Zidu Xu, Mian Zhang et al.

2025 · 70 Zit.

Patients’ Trust in Health Systems to Use Artificial Intelligence

Paige Nong, Jodyn Platt

2025 · 48 Zit.

How Academic Medical Centers Govern AI Prediction Tools in the Context of Uncertainty and Evolving Regulation

Paige Nong, Reema Hamasha, Karandeep Singh et al.

2024 · 30 Zit.

Public Attitudes Toward Notification of Use of Artificial Intelligence in Health Care

Jodyn Platt, Paige Nong, Glòria Carmona et al.

2024 · 22 Zit.

Impact of Different Approaches to Preparing Notes for Analysis With Natural Language Processing on the Performance of Prediction Models in Intensive Care

Malini Mahendra, Yanting Luo, Hunter Mills et al.

2021 · 14 Zit.

Public comfort with the use of ChatGPT and expectations for healthcare

Jodyn Platt, Paige Nong, Renée Smiddy et al.

2024 · 14 Zit.

Perceptions of precision medicine among diverse dementia caregivers and professional providers

Joseph E. Gaugler, Hayley R McCarron, Lauren Mitchell

2019 · 12 Zit.

Benchmarking of Large Language Models for the Dental Admission Test

Yu Hou, Jay Patel, Liya Dai et al.

2025 · 10 Zit.

Uptake of Generative AI Integrated With Electronic Health Records in US Hospitals

Jordan Everson, Paige Nong, Chelsea Richwine

2025 · 7 Zit.

Equity and AI Governance at Academic Medical Centers

Paige Nong

2024 · 6 Zit.

Public perspectives on the use of different data types for prediction in healthcare

Paige Nong, Julia Adler‐Milstein, Sharon L. R. Kardia et al.

2024 · 6 Zit.

The urgency of centering safety-net organizations in AI governance

Paige Nong, Eric Maurer, Roli Dwivedi

2025 · 5 Zit.

Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare

Bryan A. Sisk, Alison L. Antes, Sunny C. Lin et al.

2024 · 4 Zit.

How patients distinguish between clinical and administrative predictive models in health care

Paige Nong

2024 · 2 Zit.

MTLNFM: A Multi-Task Framework Using Neural Factorization Machines to Predict Patient Clinical Outcomes

Rui Yin, Jiaxin Li, Qiang Yang et al.

2025 · 1 Zit.