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American Roentgen Ray Society Clinical Implementation of Artificial Intelligence 2025

American Roentgen Ray Society Clinical Implementation of Artificial Intelligence 2025

Regular price $119.00 USD
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Multi Speciality

Yes

Primary Speciality

Diagnostic-Imaging

Target Audience

radiologists, imaging scientists, and healthcare professionals

Content Type

Mixed (Video + PDF)

Size

Mixed (Video + PDF)

Year

Provider/Organization

Other

  • Target Audience: radiologists, imaging scientists, and healthcare professionals
  • Sample video: contact me for sample video
  • Information:

September 15, 2025

Learning Outcomes and Modules

After completing this course, the learner should be able to:

Critically assess and select AI tools aligned with clinical needs.

Develop strategies to maximize return on investment in AI.

Implement effective methods to monitor the impact of AI tools on clinical practice.

The American Roentgen Ray Society (ARRS) – Clinical Implementation of Artificial Intelligence 2025 program is best for radiologists, imaging scientists, and healthcare professionals who want to understand how AI can be practically integrated into daily radiology workflows. It emphasizes real‑world applications, evidence‑based evaluation, and strategies for safe, effective adoption of AI tools in clinical practice.

Who Should Attend

Radiologists across subspecialties seeking to incorporate AI into diagnostic imaging.

Residents & fellows in radiology learning how AI impacts training and practice.

Medical physicists & imaging scientists developing or validating AI algorithms.

Healthcare administrators & IT leaders overseeing AI implementation in hospital systems.

What You’ll Learn

AI in radiology workflows: triage, detection, segmentation, and reporting.

Clinical validation: evaluating accuracy, reproducibility, and limitations of AI tools.

Integration strategies: how to safely implement AI in PACS/RIS systems.

Ethical & regulatory considerations: patient safety, bias, and FDA/CE approvals.

Case‑based instruction: examples of AI improving efficiency and diagnostic precision.

Future directions: evolving AI applications in radiology and multidisciplinary care.

  • Topics:

Overview of Clinical Implementation Considerations and Challenges—Manisha Bahl

Selection of AI Tools—Mark Hammer

Best Practices for Successful Deployment of AI—Avishkar Sharma

Clinical Implementation Considerations: An International Perspective—Federica Vernuccio

Lessons Learned from Clinical Implementation—Jason Wiesner

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