Aidoc

Am BG Klinikum Unfallkrankenhaus Berlin (ukb), einem spezialisierten Schlaganfallzentrum, verbindet ein KI-unterstütztes Hub-and-Spoke-Modell die radiologischen Arbeitsabläufe im gesamten Netzwerk und hilft dabei, potenziell kritische Fälle bereits beim Eingang der Bildgebung zu identifizieren und priorisieren. In einem neuen Artikel beleuchten Prof. Dr. med. Sven Mutze und Alexander Böhmcker, wie KI die vernetzte Schlaganfallversorgung unterstützen kann – von Priorisierung und Verlegungsentscheidungen bis hin zur Integration in bestehende klinische und IT-Infrastrukturen. Die Auswirkungen am ukb im Überblick: ⏱ 21 Minuten kürzere mediane Wartezeit bei KI-priorisierten Untersuchungen 🧠 12,2 % mehr erkannte intrakranielle Blutungen, wenn KI die radiologische Befundung ergänzt 📘 Über 430.000 durch KI verarbeitete Patientenuntersuchungen seit 2020 „KI verschafft uns durch die Benachrichtigung und Priorisierung kritischer Pathologien einen erheblichen Zeitgewinn", sagt Prof. Mutze. Den vollständigen Artikel lesen: https://lnkd.in/gDHUkPbC/?utm_campaign=GermanStrokeinGerman-Sept2026&utm_source=linkedin&utm_medium=paid&utm_id=1227249003&hsa_acc=511099861&hsa_cam=1227249003&hsa_grp=895480173&hsa_ad=1567039403&hsa_net=linkedin&hsa_ver=3

At the BG Klinikum Unfallkrankenhaus Berlin (ukb), a specialist stroke centre, an AI-supported hub-and-spoke model connects radiology workflows across the network, helping identify and prioritise potentially critical cases as imaging arrives for review. In a new article, Prof. Dr. med. Sven Mutze and Alexander Böhmcker explore how AI can support connected stroke care, from prioritisation and transfer decisions to integration with existing clinical and IT infrastructure. The impact at the ukb includes: ⏱ 21-minute reduction in median waiting time for AI-prioritised studies 🧠 12.2% more intracranial haemorrhages identified when AI complemented radiologist interpretation 📘 430,000+ patient studies processed since 2020 “AI potentially gives us a significant time gain through the notification and prioritisation of suspected critical pathologies,” says Prof. Mutze. Read the full article: https://lnkd.in/gRAXt9mD/?utm_campaign=GermanStrokeinEnglish&utm_source=linkedin&utm_medium=paid&utm_id=1227285713&hsa_acc=511099861&hsa_cam=1227285713&hsa_grp=895451523&hsa_ad=1572185383&hsa_net=linkedin&hsa_ver=3

Nine years ago, when two friends and I set out to build Aidoc, the vision was simple but ambitious: Could AI one day become part of the clinical fabric of healthcare — easing the burden on care teams, helping physicians be more effective despite the constraints, and ultimately saving lives? Last week, that vision took another big step forward. The FDA granted Breakthrough Device Designation to our multi-triage AI solution — the first of its kind to cover numerous suspected acute, life-threatening conditions in CT scans, all within a single workflow. We're grateful to the FDA for everything they're doing to innovate. What this means is we will have an expedited review process for more comprehensive devices. What excites me most isn’t the technology itself; it’s what this means for patients and providers. Breaking bottlenecks that delay care, supporting overburdened clinical teams, and moving toward a future where no critical finding is missed. This is just the beginning Read more here: https://okt.to/kjntgN

Excited to announce that I’ll be speaking at #HLTHUSA —healthcare’s #1 innovation event! I’m honored to join such a impressive lineup of leaders that are shaping the future of healthcare. This year, we’re building smarter healthcare, stronger connections, and bigger impact. Learn more and register: https://okt.to/Xqzj06

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