UMass Memorial Medical Center

Use of Artificial Intelligence-Based Software as Medical Devices for Chest Radiography: A Position Paper from the Korean Society of Thoracic Radiology

Eui Jin Hwang, Jin Mo Goo, Soon Ho Yoon et al.

2021 · 43 Zit.

Focused Peer Review: The End Game of Peer Review

Sarwat Hussain, Jawad Hussain, Adib R. Karam et al.

2012 · 22 Zit.

Qualifying Certainty in Radiology Reports through Deep Learning–Based Natural Language Processing

Feifan Liu, Peng Zhou, Steven J. Baccei et al.

2021 · 19 Zit.

Improving Communication of Actionable Findings in Radiology Imaging Studies and Procedures Using an EMR-Independent System

Steven J. Baccei, Cole DiRoberto, J Greene et al.

2019 · 11 Zit.

AI tools in Emergency Radiology reading room: a new era of Radiology

Sathish Kumar Dundamadappa

2023 · 7 Zit.

Cross-Check QA: A Quality Assurance Workflow to Prevent Missed Diagnoses by Alerting Inadvertent Discordance Between the Radiologist and Artificial Intelligence in the Interpretation of High-Acuity CT Scans

Mariam Chekmeyan, Steven J. Baccei, Elisabeth R. Garwood

2023 · 7 Zit.

Improving the Transcription of Patient Information From Image Requisitions to the Radiology Information System

Cole DiRoberto, Crystal Lehto, Steven J. Baccei

2016 · 6 Zit.

Utility of Large Language Models to Produce a Patient-Friendly Summary From Oncology Consultations

Ryan Holstead

2024 · 5 Zit.

Beyond Shared Decision-Making: Integrating Coproduction, Learning Health Systems, Artificial Intelligence, and Workforce Development for Patient-Centered Care

Kolu S Baysah Clark, Elaine Rudell, David Setiadi et al.

2024 · 3 Zit.

The Creative Urge

Regina Raboin

2023 · 0 Zit.

The augmented physician: AI and the future of clinical cognition

Khayreddine Bouabida, Breitner Gomes Chaves, Enoch Anane

2026 · 0 Zit.

Artificial Intelligence in Surgical Research: Transformative Impacts and Evolving Ethical Challenges

Miranda X. Morris, Faris Rustom, Benjamin D. Chun et al.

2025 · 0 Zit.

462: USING ARTIFICIAL INTELLIGENCE TO PREDICT WHICH PATIENTS ARE NOT GOING TO DETERIORATE

Itai M. Pessach, Ofer Chen, Ornah Rosenberg et al.

2021 · 0 Zit.

COVID-19 rapid tests can breed confusion – here’s how to make sense of the results and what to do, according to 3 testing experts

Nathaniel Hafer, Apurv Soni, Yukari C. Manabe

2022 · 0 Zit.

S549 Disconnect Between Perceptions of Artificial Intelligence and Adenoma Detection Rate at a Tertiary Center: Survey and Retrospective

Garrick Gu, Taylor Seacor, Sarah M. Hyder et al.

2024 · 0 Zit.