Realtime Intelligence Improves Scan Workflow Efficiency

💻 Make #DigitalPathology Your New Routine! #Digitization is profoundly transforming practices in #histology. Remote collaboration, instant access to digital slides, workflow optimization, artificial intelligence… the opportunities are numerous. To fully leverage these benefits, the laboratory information system (#LIS) plays a central role. With #TDHistoCyto, TECHNIDATA offers a solution that connects the different stages of the diagnostic pathway and facilitates the adoption of Digital Pathology: 🔹 Seamless integration with leading image management systems (#IMS) 🔹 Automatic synchronization of patient data and imaging records 🔹 Complete #traceability of every action performed on digital slides 🔹 Case validation from the laboratory or remotely 💡 Digital pathology does not replace the expertise of #pathologists; it empowers them to be even more efficient, collaborative, and responsive. How far has your laboratory progressed in its transition to digital pathology? Contact us! #TECHNIDATA #DigitalPathology #Innovation #LIS #LIMS

The healthcare industry is seeing significant consolidation, with large organizations acquiring others, leading to complex strategic decisions. These decisions require input from various stakeholders, not just clinical teams, but also crucial support functions that enable operations. Furthermore, integrating diverse workflows across different medical specialties presents challenges, particularly concerning data quality and standardization. An accession number in radiology, for instance, differs from a case number in pathology, necessitating a sophisticated approach to data construction for meaningful use. As imaging technologies evolve with concepts like 'tiles' replacing traditional frames, it's essential to adapt enterprise imaging strategies. This involves understanding each department's unique needs and providing applications that support their specific workflows, rather than expecting them to conform to radiology-centric constructs. Ultimately, the goal is to enable departments to work effectively within their own frameworks. #HealthcareIT #EnterpriseImaging #DigitalHealth #DataQuality #HealthcareStrategy #SIIMAnnualMeeting

What makes the #MOTIV™ model powerful isn’t just the data — it’s what happens around it. During the latest #CircleHour, surgeons didn’t just review results — they: ➡️ Challenged each other’s assumptions ➡️ Compared recovery protocols ➡️ Shared what’s working (and what isn’t) This kind of live, peer-to-peer learning, grounded in real #patientoutcomes, is rare in healthcare. It’s not static research. It’s not delayed insight. ✔️ It’s continuous clinical improvement in motion. If you're interested in exploring this approach or joining the conversation, reach out to learn more: https://lnkd.in/ehVpK-Qe #PhysicianCollaboration #MedTech

This is what meaningful progress in healthcare actually looks like. Not just collecting data — but creating the space for honest discussion, peer challenge, and shared learning. When clinicians come together around real outcomes, improvement becomes continuous, not episodic. It’s a powerful reminder that innovation isn’t only about technology — it’s about how we use it together. If you’re thinking along similar lines, feel free to reach out.

One of the greatest opportunities in musculoskeletal research is expanding the role of private practice physicians in generating meaningful real-world evidence. Initiatives like MOTIV™ are helping create that opportunity - bringing together clinical collaboration, shared learning, and standardized outcomes to advance research while improving patient care. I look forward to continuing to work alongside the orthopaedic community as we explore new ways to strengthen research through real-world evidence. If you’re interested in learning more about MOTIV™ or joining the conversation, I’d welcome the opportunity to connect. Lee Grossman, Andrew Wickline, John J. Mercuri, MD, MA, Michael P. Tierney, Alyssa Johncola #OREF #MOTIV #OrthopaedicResearch #RealWorldEvidence #PrivatePractice #RegenMed #PatientOutcomes

1,430 AI clearances in the US. Fewer than 1 in 10 NHS imaging departments use one beyond a pilot. Both numbers are real, and the gap between them was the honest subject of six talks at HLTH Europe.Rad in Amsterdam. Three things worth acting on: 1. Treat clearance count as a vanity metric. Dr Hugh Harvey (Hardian Health): almost every radiology clearance is a predicate me-too device, and the adverse-event tables are empty, which signals weak surveillance, not proven safety. 2. Ask a vendor for outcome evidence and an implementation plan, not a certificate. Kicky van Leeuwen (Romion Health): about 300 hours of work to field one tool, and a third of products have no publication at all. 3. Validate on your own population. Michail Klontzas, MD, PhD (University of Crete): only about 2 percent of practices use AI routinely, and the Epic sepsis model passed on paper and failed in the ward. Dr. Franz MJ Pfister, MD, MBA (deepc) showed a 10,000-study trial where AI barely moved accuracy and turnaround actually rose. Henrik Agrell (Unilabs) closed the loop: governance begins before procurement, and you select tools on your own safety data, not the vendor slide. Cleared, adopted and proven are three different purchases. Buy proof, not clearance. Swipe for the full set with sources. More of this weekly in The Imaging AI Brief, link in my profile. #radiologyAI #ClinicalAI #EUAIAct #medicalimaging #PatientSafety #aiinhealthcare

Structured reporting is shaping the future of pathology, and it's about much more than standardization. Join Peter O'Toole, President and Chief Software Architect at mTuitive, and Dr. Aleks Zuraw on the Digital Pathology Place podcast as they discuss how structured reporting improves workflows, strengthens data quality, supports compliance, and powers precision medicine and clinical decision support. If you're interested in digital pathology, healthcare innovation, or the future of diagnostic reporting, this episode is worth a listen. 🎧 Listen now: https://lnkd.in/gtEPc-Uu #mTuitive #StructuredReporting #Futureofpathology #workflow

Structured reporting is more than compliance. It's the foundation for AI, analytics, research, and better cancer care for patients. Excited to see where pathology is headed. This is worth a listen. #StructuredReporting #Pathology #HealthcareInnovation

Did you know that the integration of artificial intelligence in diagnostic imaging is significantly reducing the time required to detect early-stage pathologies? As of July 2026, clinical studies confirm that AI-assisted screenings are improving diagnostic accuracy rates by identifying patterns invisible to the human eye, allowing medical professionals to intervene much earlier than previously possible. Furthermore, the shift toward proactive, data-driven preventive care is transforming patient outcomes. We are moving away from reactive treatments toward personalized medicine models that anticipate health risks based on individual biometric trends rather than generalized averages. At MALINERMD, we believe this evolution in professional medicine is the most significant leap forward for patient longevity in the last decade. Staying at the forefront of these technological advancements is not just a competitive advantage; it is a clinical imperative. As the landscape of global healthcare continues to shift, understanding how to synthesize these digital tools with traditional medical expertise becomes essential for any practitioner looking to provide the highest standard of care. We are committed to bridging the gap between cutting-edge medical innovation and practical clinical application. At MALINERMD, our focus remains on empowering medical professionals to navigate this rapidly changing environment with confidence and precision. Are you staying updated on the latest breakthroughs in clinical technology? Follow us for more tips and insights on the future of professional medicine. 🩺 #MALINERMD #HealthTech #MedicalInnovation #DigitalHealth #ProfessionalMedicine

The Stanford-Harvard ARISE Lab just released their NOHARM Vol. 2 study, which basically stress-tests clinical AI on real-world medical cases with patient safety as the main focus. 🥁 Thumb roll: AMBOSS LiSA ranked #1 While a lot of big tech generalist models are carrying around a 10 % severe error rate, LiSA kept it to just 2.9 %.  In medicine, this difference is crucial! It determines whether a critical detail is detected or completely overlooked. Check out the study for more details: https://lnkd.in/dEPGFkH8 Honestly, this is why I’m so proud to be at AMBOSS. While the rest of the tech world is shouting about who is faster or flashier, our team of physicians and engineers has just been quietly focusing on what actually matters: not harming patients and building tools clinicians can actually trust. Huge shoutout to everyone on the team who made this happen 👏🏻