Marco Evangelos Biancolini’s Post

𝐄𝐧𝐡𝐚𝐧𝐜𝐢𝐧𝐠 𝐏𝐫𝐨𝐬𝐭𝐡𝐞𝐭𝐢𝐜 𝐃𝐞𝐬𝐢𝐠𝐧 𝐰𝐢𝐭𝐡 𝐀𝐈 We’re glad to revisit a paper published in MDPI that continues to hold relevance: "𝘗𝘳𝘰𝘴𝘵𝘩𝘦𝘵𝘪𝘴𝘵-𝘚𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘙𝘦𝘤𝘵𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘛𝘦𝘮𝘱𝘭𝘢𝘵𝘦𝘴 𝘉𝘢𝘴𝘦𝘥 𝘰𝘯 𝘈𝘳𝘵𝘪𝘧𝘪𝘤𝘪𝘢𝘭 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 𝘧𝘰𝘳 𝘵𝘩𝘦 𝘋𝘪𝘨𝘪𝘵𝘢𝘭 𝘍𝘢𝘣𝘳𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘊𝘶𝘴𝘵𝘰𝘮 𝘛𝘳𝘢𝘯𝘴𝘵𝘪𝘣𝘪𝘢𝘭 𝘚𝘰𝘤𝘬𝘦𝘵𝘴" by Andrea G. Cutti, Maria Grazia Santi, Andrew H. Hansen, Stefania Fatone, and the Residual Limb Shape Capture Group. The study addresses a critical aspect of prosthetics—the socket, the most patient-specific element of a prosthesis. Traditionally, creating a custom socket involves manual rectification of a plaster model, which is not only time-consuming but also relies heavily on the implicit expertise of prosthetists, leading to variability. 𝐓𝐡𝐢𝐬 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐯𝐞 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞𝐬 𝐚𝐧 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐭𝐨 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐩𝐫𝐨𝐬𝐭𝐡𝐞𝐭𝐢𝐬𝐭-𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐭𝐞𝐦𝐩𝐥𝐚𝐭𝐞𝐬, 𝐰𝐡𝐢𝐜𝐡 𝐜𝐚𝐧 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐫𝐞𝐜𝐭𝐢𝐟𝐲 𝐭𝐫𝐚𝐧𝐬𝐭𝐢𝐛𝐢𝐚𝐥 𝐫𝐞𝐬𝐢𝐝𝐮𝐚𝐥 𝐥𝐢𝐦𝐛 𝐬𝐡𝐚𝐩𝐞𝐬. By utilizing a training dataset and unsupervised learning, the AI algorithm successfully replicates a prosthetist's rectification process with impressive precision and consistency. 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✔︎ The AI-rectified models showed excellent agreement with prosthetists' manual adjustments. ✔︎ The process demonstrates potential for significant time savings while maintaining quality. ✔︎ It offers a promising leap forward in the digital fabrication of prosthetic sockets. This paper not only underscores the transformative potential of AI in prosthetics but also serves as a proof-of-concept for integrating AI into clinical workflows. It’s a must-read for anyone interested in the intersection of healthcare, engineering, and AI. 📖 𝑫𝒐𝒘𝒏𝒍𝒐𝒂𝒅 𝒕𝒉𝒆 𝒑𝒂𝒑𝒆𝒓 𝒉𝒆𝒓𝒆: https://lnkd.in/d6j44-5t #Prosthetics #AI #DigitalHealth #Innovation #Healthcare #Engineering #RBFMorph https://lnkd.in/d6j44-5t

Computer vision and AI technology is gaining momentum as the new, "must-have" technology for supply utilization. Our latest Snap&Go installation completely transformed this operating room into a digital supply documentation hub. ❗ An end to barcode frustrations. ❗ No need to key-in data. ❗ No more data gaps in your records. Our next generation technology uses computer vision, AI and machine learning algorithms to ensure full data capture straight into the EHR, including full UDI data (inc. batch number, serial number, expiry date.) 💪No reliance on your Item Master. 🔥 No implant left behind. Wanna join the AI-vision revolution? Find out how you too, can get full supply utilization records before the end of surgery, and use AI-driven analytics for more efficient OR and supply chain management. 👉 https://lnkd.in/dc5zVPjA #AIRevolution  #AItechnology #aiautomation  #DataDrivenHealthcare  #digitaltransformations #EHRoptimization #HealthcareInventoryManagement #ORsupplychain #perioperativemanagement

"The Effect of AI in Biomedical Engineering": "AI is revolutionizing biomedical engineering by enhancing diagnostics, personalizing treatments, and improving operational efficiency. Machine learning algorithms are enabling faster, more accurate diagnoses, such as detecting anomalies in medical images. In prosthetics, AI is creating smarter, more adaptive devices tailored to patients’ needs. Moreover, AI optimizes hospital operations by predicting equipment maintenance, reducing downtime, and ensuring the continuous availability of life-saving devices. As AI continues to evolve, its integration in biomedical engineering promises to improve both patient outcomes and healthcare efficiency." #BiomedicalEngineering #AIinHealthcare #MedicalInnovation #HealthcareTechnology #PatientSafety #AIRevolution #DigitalHealth #MedTech #FutureOfHealthcare #SmartMedicine

UCLA introduces SLIViT 🚨 A groundbreaking AI model for analyzing 3D medical images faster and more cost-effectively than human experts. 😳 🔍 Key highlights: 1️⃣ Analyzes MRIs, CTs, and other scans at lightning speed. 🧠 2️⃣ Handles large data sets and adapts to new imaging techniques. 📊 3️⃣ Vital for regions with limited medical imaging professionals. 🌍 4️⃣ Identifies disease markers across different scan types. 🩺 5️⃣ Outperforms existing models, making imaging more accessible. ⚡ 6️⃣ Trained on 2D images, then fine-tuned for precise 3D analysis. 🔬 7️⃣ Leverages insights from one scan type to enhance others. 🔗 With its ability to handle massive data and deliver fast results, SLIViT could be a game-changer for affordable, accurate medical imaging. 🩻💡 What are your thoughts on the future of AI in healthcare? 💬

🚀 New 3D-Printed Device Revolutionizes Blood Conductivity Testing! 🚀 Researchers unveil a cutting-edge lab-on-a-chip device that uses AI to measure blood conductivity with unmatched precision. 🌟 📊 Highlights: -Portable & Self-Powering: No bulky equipment needed. -AI Precision: Accurate predictions from voltage patterns. -Minimal Sample: Just a few drops of blood required. -Wide Applications: Beyond conductivity, measures various health parameters. Published in Advanced Materials, this innovation links blood conductivity to health conditions like electrolyte imbalances and Alzheimer's. 🩸 Design: -3D-printed with PMMA -Uses a triboelectric nanogenerator -Disposable and perfect for point-of-care 🔍 Findings: -High accuracy -Ideal for resource-limited settings -Transformative potential for diagnostics 🔗 Read the news piece here: https://lnkd.in/ef6cAWvF #MedicalInnovation #HealthTech #AI #3DPrinting #Diagnostics

[ROKIT Healthcare: AiD Regen 3D wound modeling application] AiD Regen is an advanced application that leverages AI to enhance precision and efficiency in wound modeling. This innovative tool automates the creation of wound-specific 3D printable files, seamlessly integrating with the Dr. INVIVO platform to deliver tailored regenerative solutions. Key Features of AiD Regen: ▸ Measure wound with AI: Scans and automatically detects wound shapes and dimensions with precision. ▸ Automated 3D Model Creation: Generates accurate, wound-specific 3D printable files without manual intervention. ▸ Integration with Dr. INVIVO: Sends files directly to Dr. INVIVO, enabling efficient and personalized treatment workflows. ▸ By simplifying the wound analysis process, AiD Regen empowers medical professionals with tools to provide faster and more customized care, improving outcomes for patients. #ROKITHealthcare #OrganRegeneration #SkinRegeneration #AI #Bioprinting #ModelingApplication

🌟 Exciting Announcement: Revolutionizing Prosthetics with Our Latest Project! 🌟 During my B.Tech journey in 2023, I had the privilege of leading a groundbreaking project that has the potential to transform the field of prosthetics: An Integrated Multi-modal Sensing System for Bionic Hand Control Using RNN. Watch the video below to learn more about this innovative project: This project represents a fusion of technology and compassion, aimed at improving the lives of individuals with limb differences. By leveraging electromyography (EMG) signals and flex sensors within a data glove, our bionic hand achieves unprecedented motion recognition accuracy. But what truly sets this project apart is the use of a cutting-edge Recurrent Neural Network (RNN) Deep Learning approach. By harnessing the power of artificial intelligence, we're able to interpret and respond to EMG signals with incredible precision, providing users with a level of control and dexterity that was once thought impossible. I'm incredibly proud of the work our team has done on this project, and I'm excited about the potential impact it can have on improving lives through technology. From restoring independence to enhancing quality of life, our bionic hand is a testament to the power of innovation and the boundless possibilities of human ingenuity. Stay tuned for more updates on this project and its journey toward making a meaningful difference in the world of prosthetics. Together, let's continue pushing the boundaries of what's possible and creating a future where technology serves humanity in profound ways. 💪🤖 #BionicHand #Prosthetics #Innovation #Technology #DeepLearning #Empowerment #Freelance

A new AI model by UCLA researchers can analyze medical scans 5,000x faster than human doctors with the same accuracy. By using transfer learning from 2D medical data, SLIViT(Slice Integration by Vision Transformer) overcomes the challenge of limited 3D datasets, making it capable of analyzing complex 3D scans with incredible speed and precision. What once took 8 hours now takes just 5.8 seconds. Here’s how it works: 1. Transfer learning SLIViT is pre-trained on extensive 2D medical imaging datasets, enabling it to effectively analyze 3D scans despite the limited availability of 3D datasets. 2. Fast & accurate analysis Using a ConvNeXt backbone for feature extraction and a Vision Transformer (ViT) module for combining these features, SLIViT matches the accuracy of clinical specialists. 3. Flexibility across modalities SLIViT can analyze scans from multiple modalities, including OCT, MRI, ultrasound, and CT, making it adaptable to emerging imaging techniques and diverse clinical datasets. This AI can work with smaller datasets, making it accessible even to hospitals with limited resources. It means: -Rural clinics can offer expert-level diagnostics -Life-threatening conditions are caught earlier -Millions of patients get faster care In healthcare, speed isn’t just about efficiency - it’s about survival. And if SLIViT lives up to its claims in real-world scenarios, it could be a superpower to help save more lives, faster. Could this AI breakthrough reshape the future of medical diagnostics? #ai #innovation #healthtech

𝐇𝐚𝐯𝐞 𝐲𝐨𝐮 𝐡𝐞𝐚𝐫𝐝 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐥𝐚𝐭𝐞𝐬𝐭 𝐛𝐫𝐞𝐚𝐤𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐟𝐫𝐨𝐦 𝐔𝐂𝐋𝐀? Researchers have unveiled SLIViT (SLice Integration by Vision Transformer), an innovative AI model that transforms how we analyze complex 3D medical scans. 𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐒𝐋𝐈𝐕𝐢𝐓 𝐚 𝐠𝐚𝐦𝐞-𝐜𝐡𝐚𝐧𝐠𝐞𝐫? - It efficiently analyzes 3D imaging types like MRIs, CT scans, and ultrasounds. - This model achieves expert-level accuracy while slashing analysis time by an astonishing 5,000 times! - Unlike its predecessors, SLIViT can be trained with hundreds of samples, making it practical for real-world healthcare settings. - Using transfer learning, SLIViT taps into knowledge from 2D medical data, allowing for swift and effective training with limited 3D datasets. 𝐖𝐡𝐲 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫? With healthcare systems increasingly pressed for quicker diagnostics, SLIViT could revolutionize patient care. Making expert-level imaging accessible, promises to democratize advanced medical analysis for providers with fewer resources. Could SLIViT be the future of medical imaging? #AI #HealthcareInnovation #MedicalImaging #UCLA #SLIViT

🚀 Exciting breakthrough in medical imaging AI! 🏥🖥️ Researchers at MIT and Massachusetts General Hospital have developed InstaLabel, a game-changing AI tool that's revolutionizing how doctors annotate medical scans. Here's why it's making waves: ✅ Slashes annotation time by up to 70% ✅ Achieves 95% accuracy in identifying anatomical structures ✅ Trained on 100 abdominal CT scans ✅ Adapts to various imaging types with minimal retraining InstaLabel empowers doctors to annotate 3D scans using simple 2D scribbles and can label multiple organs simultaneously. This innovation could lead to faster diagnoses and improved patient care. As the team expands InstaLabel's capabilities, we're looking at a future where AI significantly accelerates and enhances medical imaging analysis. Image credit: Alex Shipps/MIT CSAIL with elements from Pixabay, and the researchers. Follow Leon Zheng to join the unique journey of AI! #MedicalAI #HealthcareTech #AIInnovation #MedicalImaging