Kickoff speaker Dr. Benoit Desjardins looks at how AI is increasing cybersecurity risk. The HIMSS AI and Cybersecurity Virtual Forum on Tuesday, November 18, represents the next step in AI progression, from excitement after…
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What You Should Know:
– Butterfly Network, Inc. (“Butterfly”), a digital health company specializing in whole-body ultrasound imaging, has launched Compass AI™.
– The challenge in POCUS has long been the reliance on traditional, radiology-style, order-based…
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AI-driven vision will restore operational balance to radiology | Healthcare IT News
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Three of UK healthcare’s most influential voices will speak at Digital Health Rewired 2026 to provide guidance on how to harness AI safely, ethically and effectively.
Professor Alastair Denniston, professor of regulatory science and innovation…
AI is transforming healthcare, yet pediatric adoption remains limited and governance is underdeveloped. We review existing frameworks and identify pediatric-specific gaps: insufficient stakeholder engagement, developmentally appropriate consent/assent, limited bias mitigation, and unclear accountability. An…
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Image Credit: SimonMed
What You Should Know:
– SimonMed Imaging, one of the largest outpatient medical imaging providers and radiology practices in the United States, today announced the launch of Ultrasound+, an AI-enabled ultrasound program.
– The…
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Harmonized ONcologY Biomedical Embedding Encoder (HONeYBEE) is an open-source framework that integrates multimodal biomedical data for oncology applications. It processes clinical data (structured and unstructured), whole-slide images, radiology scans, and molecular profiles to generate…
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Core Clinical & Diagnostic Innovations
Real-World Evidence (RWE) Agent Pilot: Atropos Health, in collaboration with Microsoft, is piloting the Atropos Evidence™ Agent at Stanford Health Care. This expert agent generates patient-specific RWE integrated into the…
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Te Whatu Ora on the lookout for radiology AI orchestration solution | Healthcare IT News
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Artificial intelligence (AI) tools for radiology are commonly unmonitored once deployed. The lack of real-time case-by-case assessments of AI prediction confidence requires users to independently distinguish between trustworthy and unreliable AI predictions, which increases…
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