Tsinghua University launches AI-powered hospital in China

🚑✨ Tsinghua’s AI Agent Hospital: The Future of Healthcare is Self-Evolving Tsinghua University has launched the world’s first AI Agent Hospital — a virtual medical ecosystem where every doctor, nurse, and patient is an autonomous AI agent. Here’s why this matters 👇 🔹 End-to-End Simulation: From triage → consultation → diagnosis → treatment → rehab. 🔹 Self-Learning Agents: Trained on tens of thousands of virtual patients, improving with each case. 🔹 Early Wins: Agents reached 93% accuracy on MedQA respiratory benchmarks after ~10k patients. 🔹 Real Pilots: Already active in general practice, ophthalmology, radiology, and respiratory care. 💡 The big picture: Hospitals could evolve into AI-driven ecosystems where patient care, physician training, and research all happen in one continuous loop. This isn’t AI as a tool — it’s AI as a co-architect of healthcare systems. #AIinHealthcare #ArtificialIntelligence #DigitalHealth #HealthTech #MachineLearning #Tsinghua #FutureofMedicine #AIAgent #MedTech #HealthcareInnovation

AI + Data in Healthcare: Some thoughts AI is no longer a future concept in medicine — it’s here. In 2024, 2 out of 3 U.S. doctors said they already use AI tools, up nearly 80% from the previous year. Around 65% of hospitals use predictive models tied to patient records for decisions. AI is already helping detect conditions like diabetic retinopathy and speeding up radiology reporting. But the big question is: how do we balance efficiency with empathy? Health is personal — patients want both smart insights and human connection. I believe the real value of AI in MedTech will come when we integrate diverse data (labs, images, notes) while keeping trust, transparency, and patient experience at the center. #AI #Healthcare #MedTech #DataIntegration

Something’s Cooking in Healthcare: September’s AI Lineup • Sep 1 — Madrid, Spain — ESC Congress 2025 (cardiology; AI-heavy sessions). • Sep 8–10 — Cambridge, UK — AIiH: Artificial Intelligence in Healthcare 2025. • Sep 9–10 — Basel, Switzerland — Intelligent Health 2025. • Sep 10–12 — Rotterdam, Netherlands — Responsible AI in Health Care. • Sep 15–17 — Boston (Everett), USA — World Medical Innovation Forum (WMIF). • Sep 15–19 — Vienna, Austria — EASD 2025 (Diabetes; AI & analytics tracks). • Sep 16–17 — Philadelphia, USA — DPHARM 2025 (clinical-trials innovation with AI/ML). • Sep 22–25 — Houston, USA — AI in Health Conference (Rice Univ./Ken Kennedy Institute). • Sep 23–24 — Boston, USA — Innovate Health (care delivery; strong clinical AI content). • Sep 23–27 — Daejeon, South Korea — MICCAI 2025 (premier medical imaging/AI).

BrainScan S.A. implements its AI system at John Paul II Specialist Hospital in Cracow. We are delighted to announce the deployment of our advanced AI system for brain CT analysis at the John Paul II Specialist Hospital in Cracow. Our shared goal is to bring innovative AI-driven solutions into daily clinical practice, supporting physicians in medical imaging diagnostics and accelerating clinical decision-making. Partnering with one of the leading medical centers in Poland is both an honor and a significant step forward in making modern technologies more accessible in healthcare. Through this cooperation, we aim to support specialists in their daily practice more effectively and contribute to improving the quality and availability of patient care. This is an important milestone on the path toward digital transformation in medicine, where people and technology move forward hand in hand. #AI #medtech #healthcare #BrainScan #innovation #diagnostics #deployment

Machine-learning tool gives doctors a more detailed 3D picture of fetal health | MIT News MIT researchers have introduced "Fetal SMPL," a machine-learning tool designed to produce precise 3D models of fetal development using MRI data. Trained on 20,000 scans, it accurately predicts fetal size, shape, and movement, enabling clinicians to identify potential abnormalities with unprecedented clarity. Unlike traditional 2D ultrasounds and limited 3D MRI interpretations, Fetal SMPL overcomes challenges stemming from the fetus's constrained environment, offering accurate alignment and measurements. This groundbreaking approach has the potential to revolutionize prenatal diagnostics, paving the way for more detailed assessments of fetal health. As AI continues to enhance healthcare, advancements like these remind us of technology's transformative power. Learn more at: https://lnkd.in/eftqwaGq What are your thoughts on this? Don't hesitate to share your thoughts and ideas in the comments below. DevTech is always eager to hear from our community and learn about your experiences and perspectives. Looking forward to connecting with you! #devtech.pro #AI #technology #trending #news #innovation #technology This article is written and published by Doki. Doki is our documentation's and social media's AI Agent.

🩺 𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐈𝐦𝐚𝐠𝐢𝐧𝐠, 𝐒𝐮𝐩𝐞𝐫𝐜𝐡𝐚𝐫𝐠𝐞𝐝 𝐰𝐢𝐭𝐡 𝐀𝐈 Imagine an AI that doesn't just analyze medical scans but actually creates training data for rare conditions that doctors might see once in their careers. Here's what's happening right now: → 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 spots tumors, lung infections, and retinal anomalies faster than human eyes. → 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 creates synthetic medical images for training when real cases are too rare. → 𝐈𝐦𝐚𝐠𝐞 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭 turns blurry scans into crystal-clear diagnostics. → 𝟐𝐃 𝐭𝐨 𝟑𝐃 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 helps surgeons plan complex operations. The game changer? We're solving the data scarcity problem in healthcare. Instead of waiting years to collect enough cases of rare diseases, AI generates realistic training scenarios instantly. This means rural hospitals can utilize AI-powered diagnostic tools that rival those of top medical centers. Want to explore this tech for your hospital or clinic? 𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬. #MedicalImaging #RadiologyAI #HealthcareInnovation #SmartHospitals #AIforDoctors #SyntheticData #GenerativeAI #FutureOfHealthcare #ArtificialIntelligence #ComputerVision #MedicalAI #HealthTech #AIinHealthcare #MedTech #DigitalHealth

Artificial Intelligence is making its way into physiotherapy. This article highlights how AI tools are already being used to support assessments, monitoring and patient engagement — while keeping the physiotherapist at the center of care. Exciting opportunity ahead: more objective data, better adherence, and enhanced clinical decision support. How do you see AI impacting our field? 🔗 Read more: 👉 https://lnkd.in/esB68kHd #Physiotherapy #DigitalHealth #Innovation #ArtificialIntelligence

AI + Teleradiology: A Game-Changer in Healthcare 🤖 Radiology lies at the heart of modern diagnostics — yet challenges like delayed reporting, shortage of specialists, and rising imaging volumes often limit timely care. This is where AI interfaced with Teleradiology can make a transformational impact: 🔹 Faster Turnaround – AI-powered image analysis accelerates reporting and reduces diagnostic delays. 🔹 Enhanced Accuracy – Automated detection of subtle patterns supports radiologists in minimizing errors. 🔹 24/7 Accessibility – Teleradiology ensures expert review anytime, anywhere — critical for rural and underserved regions. 🔹 Workload Management – AI triages urgent scans (like strokes or trauma), enabling radiologists to prioritize life-saving cases. 🔹 Cost-Effective Care – Streamlined workflows and reduced repeat scans lower the overall cost of healthcare delivery. The fusion of AI intelligence with remote radiology expertise not only boosts efficiency but also ensures equitable access to high-quality diagnostics, regardless of geography. 🚀 The future of healthcare imaging is smarter, faster, and more accessible — with AI-enabled Teleradiology leading the way. #AI #Teleradiology #Healthcare #DigitalHealth #MedicalImaging #Innovation #FutureOfHealthcare

Smart Reporting embeds context-aware AI into automated reporting. Medical technology manufacturer Smart Reporting GmbH says it is shaping AI use in radiology by embedding it into reporting workflows in ways that are structured, transparent and meaningful, with the mission to support radiologists, not replace them. AI-generated image analysis yields extensive data, but rather than just presenting findings Smart Reporting says it aligns data with internal decision trees and guidelines, ensuring that information is organised, clinically relevant and prepared for analytics. Content is supplemented with clinical context and quality assurance checks, while data is converted into succinct, actionable insights instead of large data dumps. “For instance, a pulmonary nodule can be categorised according to various guidelines such as Fleischner, BTS, Lung-RADS or PanCan, and the platform chooses the most appropriate model based on context and region,” the company explains. https://lnkd.in/eWBWdet6 #RADMagazine #RADLink #medicalimaging #news #healthcare #medical #radiology #AI

Medical imaging is a cornerstone of diagnosis, but traditional analysis by human experts can be slow and prone to variability. In 2025, artificial intelligence (AI) is revolutionizing the field with remarkable, life-saving results. Research led by the Universität zu Lübeck in Germany demonstrated that using AI in mammography screening boosts cancer detection by 17.6%, according to findings from their large-scale study of over 460,000 women published this January, while also reducing unnecessary patient recalls and leading to faster, more confident diagnoses. AI excels at identifying subtle patterns the human eye might miss. For instance, AI models now detect critical stroke-related hemorrhages on CT scans with 98.7% sensitivity, drastically cutting time to diagnosis in emergencies. The technology also extends to predictive analytics, forecasting disease progression for conditions like multiple sclerosis with over 80% accuracy. This transformation brings key systemic benefits: 1. Alleviating radiologist shortages by automating repetitive tasks Studies project that by 2025, AI could handle up to 50% of a radiologist’s workload, freeing experts for complex cases. 2. Improving accessibility through portable AI-powered systems Low-field MRI units such as Hyperfine | AI-Powered Portable MRI’s Swoop deliver diagnostic imaging at around 80% lower cost and can operate in underserved areas without traditional infrastructure. 3. Reducing healthcare costs through greater efficiency AI-enabled imaging workflows and digital pathology are projected to save institutions up to USD 12 million over five years. Reflecting its rapid, worldwide adoption, market projections show explosive growth for AI in medical imaging. The field is now moving beyond just sharper images to providing richer insights, integrating diverse health data to enable truly personalized medicine and a more patient-centric future. #AI #HealthTech #Innovation #Technology #Biotech #MedicalImaging #Diagnosis #Healthcare