#rsna2025

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From Chaos to Clarity - Segmed and Microsoft shared How Healthcare AI is Evolving

✅ From Traditional AI to Foundation Models Traditional AI: narrow, task-specific, heavy on supervised training Foundation Models: broad, multi-modal, adaptive with minimal fine-tuning ✅ Challenges in Accessing Medical Imaging Data Data silos and lack of standardization Complex de-identification processes Large file sizes and no easy cohort-building tools Bias from limited, non-diverse datasets ✅ What’s Needed for Foundation Models Multi-modal datasets: images, reports, clinical data Large-scale non-specific data for pre-training + smaller specific sets for tuning ✅ Segmed’s Solution Secure de-identification Searchability and cohort building Standardization across providers Expanded diversity: USA 50 states + 10 countries ✅ The Future Lower barriers to entry for AI development Broad, multi-modal models integrating radiology, pathology, and clinical history Democratizing healthcare innovation Foundation models aren’t just the future—they’re the catalyst for scalable, equitable healthcare AI. A big thank you to Ivan Tarapov, Sr. Director of Product Management for Multimodal Healthcare AI at Microsoft, for sharing his insights and vision during this session!

For more information visit: https://www.segmed.ai/resources/events

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Neusoft Medical Systems Unveils World’s First 8cm Wide-Coverage Photon-Counting CT http://dlvr.it/TPbFQq

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🚀 Segmed at RSNA 2025: Unlocking the Power of Real-World Imaging Data 🚀 We’re excited to share that Segmed is heading to RSNA 2025, where we’ll spotlight how Real-World Imaging Data (RWiD) is transforming every stage of the AI lifecycle — from Foundation Model development all the way to regulatory submission readiness. This year, we’re proud to be featured in a AI Theather Session with Microsoft, diving into how high-quality, tokenized, de-identified imaging data accelerates model performance, safety, and clinical reliability. 🔗 Event details: https://www.segmed.ai/events/segmed-rsna-2025 🌐 Why RWiD Matters More Than Ever Healthcare Foundation Models (HFMs) are reshaping medical AI — but real-world deployment requires more than generalized training. Clinical imaging varies dramatically by modality, equipment, demographic factors, and context. Without robust fine-tuning, even strong HFMs risk: ⚠️ Missing subtle diagnoses ⚠️ Failing to generalize across populations ⚠️ Stalling on the path to clinical validation and regulatory clearance At Segmed, we bridge that gap with the industry’s most diverse, global imaging dataset: 📊 100M imaging studies 🏥 2,000+ healthcare sites 🌎 Across 5 continents 🔐 Fully tokenized, de-identified, regulatory-ready Fine-tuning with Segmed’s RWiD enables: ✅ Higher diagnostic accuracy ✅ Diverse patient cohorts ✅ Stronger safety and performance evidence for regulatory submissions ✅ Real-world reliability that gets AI from the lab into the industry Dive deeper into how RWiD elevates HFM development in our latest blog post: 👉 https://www.segmed.ai/resources/blog/fine-tuning-healthcare-foundation-models-with-rwid If you’re building the next generation of medical AI, let’s connect at RSNA. Segmed is here to streamline your journey from Foundation Models to regulatory-grade evidence — powered by Real-World Imaging Data.