University of Minnesota Rochester

Artificial Intelligence in Cardiovascular Care—Part 2: Applications

Sneha S. Jain, Pierre Elias, Timothy J. Poterucha et al.

2024 · 51 Zit.

Battle of the (Chat)Bots: Comparing Large Language Models to Practice Guidelines for Transfusion-Associated Graft-Versus-Host Disease Prevention

Laura D. Stephens, Jeremy W. Jacobs, Brian D. Adkins et al.

2023 · 27 Zit.

Assessing the performance of Watson for oncology, a decision support system, using actual contemporary clinical cases.

Mark G. Kris, Ayca Gucalp, Andrew S. Epstein et al.

2015 · 6 Zit.

Beyond <i>Jeopardy!</i>: Harnessing IBM's Watson to improve oncology decision making.

Peter B. Bach, Marjorie G. Zauderer, Ayca Gucalp et al.

2013 · 6 Zit.

Testing the capability of generative artificial intelligence for parent and caregiver information seeking

YaeBin Kim, Silvia Vilches, Sidney Shapiro et al.

2025 · 2 Zit.

1214: Development and Verification of a Digital Twin Patient Model to Predict Treatment Response in Sepsis

Amos Lal, Guangxi Li, Edin Cubro et al.

2020 · 1 Zit.

Guidelines and Checklists for Artificial Intelligence (AI) in Surgical Education Research: A Comprehensive Narrative Review

Caitlin Silvestri, Darian L Hoagland, John M. Woodward et al.

2025 · 0 Zit.

AI and Nursing

Jonathan Meyers

2024 · 0 Zit.

Artificial Clinic Intelligence (ACI): A Generative AI-Powered Modeling Platform to Optimize Patient Cohort Enrichment and Clinical Trial Optimization

Choong-Yong Ung, Cristina Correia, Z M Zhang et al.

2025 · 0 Zit.

Appraising the value of AI in wrist fracture detection: A clinical review

A E Gharavi, Sergio M. Navarro, Andy Tom et al.

2026 · 0 Zit.