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How to Build a Business Case for Radiology AI (Using Symbe)

🚀 Ready to build a business case for AI at your hospital? Book a free call → https://www.newtonstree.ai/contact?ut...

Creating a business case for AI is not just about proving that an algorithm is accurate. It is about showing how the technology will meaningfully improve care, save time, reduce costs, and increase capacity inside your organisation. And the best way to do that is by walking through the full chain of clinical and operational impact.

In this video, Haris Shuaib, NHS Medical Physicist and CEO at Newton’s Tree, explains how to build a compelling business case for radiology AI using Chest X-ray AI as an example, with our parters Symbe.

In this video you’ll see how to define the clinical problem clearly, map how AI fits into the radiology workflow, and quantify benefits grounded in operational reality. These include reduced turnaround times, backlog reduction, lower overtime and outsourcing spend, increased reporting capacity, and more efficient deployment using a managed platform.

The key takeaway: A strong radiology AI business case connects clinical need, workflow integration, and measurable operational value into a clear narrative decision-makers can trust.

📺 Watch the full video here:    • How to Build a Business Case for Radiology...  
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🔔 VIDEO CHAPTERS
00:00 Intro: Why AI business cases go beyond accuracy
00:32 Step 1 – Define the clinical problem
00:53 Step 2 – Fit AI in the workflow
01:12 Step 3 – Quantify the benefits
03:18 Step 4 – Consider risks and enablers
03:52 Summary
04:16 How Newton's Tree can help
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💬 How does your organisation approach building business cases for healthcare AI? Which operational metrics matter most in your setting?
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