Course Syllabus: AI as the Second Set of Eyes

Course Syllabus: AI as the Second Set of Eyes

by Hurraira Adrees -

Dear Dr. Nellie and Colleagues,

I am pleased to share the syllabus for my practice course, which I have developed with the help of several AI tools. I have attached the full Microsoft Word version of the document to this post for a more detailed view.

Course Overview:

  • Title: AI as the Second Set of Eyes: Artificial Intelligence in Medical Imaging for Radiologic Technologists
  • Target Learners: Registered Radiologic Technologists and students
  • Goal: To equip professionals with the knowledge to evaluate and collaborate with AI tools that identify imaging "red flags" like fractures and nodules.

Tool Comparison & Preference: To create this draft, I experimented with Claude, Microsoft Copilot, and Gemini. While all provided useful insights, I preferred Claude for its ability to structure the four weekly modules and learning outcomes with high clinical precision.

Weekly Highlights:

  • Week 1: Foundational principles and how AI "sees" images
  • Week 2: Focus on specific red flags like intracranial hemorrhage and pulmonary nodules
  • Week 3: Practical integration and the technologist's role in the workflow
  • Week 4: Ethics, algorithmic bias, and the future of the profession
  • Assessment Strategy: To ensure learners effectively master these concepts, I have established the following grading structure:
Assessment Component Due Date Weight
Weekly Quizzes (Weeks 1–3) End of each week

30%

Week 2: Mini-Case Assignment End of Week 2

15%

Week 3: Workflow Reflection (400 words) End of Week 3

20%

Week 4: Final Portfolio (600 words) End of Week 4

25%

Discussion Forum Participation Ongoing

10%

I have attached the full AI_Second_Set_of_Eyes_Syllabus.docx to this post for more detailed information on learning outcomes and activities.

Please find the full AI_Second_Set_of_Eyes_Syllabus.docx attached below:

I look forward to building this course out further in our practice area and seeing how everyone else is utilizing these powerful AI tools to shape their own teaching!

Warm regards,

Jaweria

Course Syllabus: AI as the Second Set of Eyes

by Jurix Rivero -

Hi, Jaweria,

Thank you for sharing your syllabus. I think your course is very interesting and well organized. The topic of AI in medical imaging is very relevant for radiologic technologists today, especially because AI is becoming more common in all fields of healthcare.

I also like how you included both practical and ethical aspects on weeks 3 and 4, such as workflow integration and algorithmic bias. The weekly structure and assessment strategy are clear and balanced for learners.

It was interesting to read your comparison of Claude, Copilot, and Gemini. Your explanation about why you preferred Claude was very clear.

Overall, this looks like a professional and engaging course. Well done!

Thanks for sharing!

Kind regards,

Jurix

Course Syllabus: AI as the Second Set of Eyes

by Dr. Nellie Deutsch -

Thank you for sharing your excellent course syllabus, Jaweria. Please review the instructions once again and add 2 more sections. 

Re: Syllabus Resource Finalized – Jaweria

by Hurraira Adrees -

Dear Dr. Nellie and Colleagues,

Thank you for the excellent feedback! I have reviewed the core instructions and updated my syllabus to explicitly include the two missing required sections to ensure a comprehensive curriculum framework.

To achieve this, I collaborated with Claude and utilized EnterPro to carefully redistribute my clinical content into a robust 6-week timeline while keeping our core assessment weights intact. EnterPro was incredibly helpful in formatting the structural alignment, while Claude ensured high clinical precision for our target learners.

Here are the two newly added sections now integrated into the curriculum:

1. New Section: Required Learning Resources & Technical Requirements

To ensure radiologic technologists can seamlessly engage with the AI software simulations, this section outlines necessary browser compatibility (HTML5 supported browsers) and open-access medical imaging datasets (such as RSNA and Cancer Imaging Archive) that will be utilized for hands-on nodule and fracture detection practice.

2. New Section: Academic Integrity & AI Use Policy in Clinical Education

Given the subject matter, this section establishes clear guardrails on how students can ethically use generative AI for brainstorming and reflection drafting while strictly prohibiting the use of AI to generate solutions for case study evaluations and weekly quizzes.

Updated 6-Week Course Outline Overview:

  • Week 1: Introduction to AI in Medical Imaging & Computer-Aided Detection (CAD)

  • Week 2: Deep Dive into "Red Flags" (Fracture & Pulmonary Nodule Detection)

  • Week 3: Practical Integration into Radiology Information Systems (RIS/PACS) Workflows

  • Week 4: Algorithmic Bias, Ethics, and Professional Accountability

  • Week 5: Future Trends, Emerging AI Models & Advanced Diagnostics

  • Week 6: Final Portfolio Showcase, Peer Evaluation, and Course Reflection

Assessment Consistency Check:

The original grading weights remain perfectly balanced across the new timeline to ensure steady student evaluation:

  • Weekly Quizzes: 30%

  • Week 2 Mini-Case Assignment: 15%

  • Week 3 Workflow Reflection: 20%

  • Week 4 Final Portfolio: 25%

  • Forum Participation: 10%

🔗 REVISED SYLLABUS ACCESS LINKS: