Cleveland Clinic Innovations’ Post

Artificial Intelligence is reshaping healthcare, but successfully implementing AI requires more than just technology—it demands strategy, validation, and practical integration. At the InnovatorMD Global Summit 2025, Srikanth M., Founder & CEO of Shree Advisory & Consulting, LLC, will share evidence-based approaches to clinical AI implementation, drawing from his extensive experience in radiology at UT MD Anderson Cancer Center and involvement with the iBCI Collaborative Community. This session will examine: 1. Real-world examples from medical imaging and neural interfaces 2. Strategies for technology assessment, regulatory compliance, and clinical workflow integration 3. Practical challenges and proven solutions for healthcare technology adoption Dr. Mahankali’s expertise spans medical imaging, clinical innovation, and regulatory science. A Health Affairs reviewer and Einstein Visa recipient, he focuses on harnessing AI and neurotechnology to improve patient care and transform clinical practice. Discover how AI can move from theory to reality in healthcare, and gain actionable insights for navigating the challenges of implementation. Join us at the InnovatorMD Global Summit 2025 to learn how to successfully integrate AI into clinical workflows and shape the future of medicine. Register Now: https://lnkd.in/gy_u-ptz Uli K. Chettipally, MD., MPH., Dominique Kim, MPH, Ignacio H. Medrano, Ricardo Gaminha Pacheco, Harvey Castro, MD, MBA., Jon Warner #AIInHealthcare #ClinicalInnovation #MedicalImaging #NeuralInterfaces #HealthcareTechnology #FutureOfMedicine

I had the pleasure of attending my first event hosted by The Business Council of Westchester last night, Healing Horizons: Navigating AI in Healthcare's Transformative Technologies. Dr. Parsa Mirhaji, Director of the Center for Health Data Innovations at Montefiore Einstein, delivered an insightful talk about the revolutionary work happening in their facility, where AI is being leveraged to enhance patient care. From matching cancer patients to clinical trials to predicting surgery cancellations and anticipating ventilator needs, the scope of AI-driven improvements is nothing short of inspiring. I feel fortunate to have such a world-class facility in our community. Dr. Mirhaji also shared some of the best analogies I’ve encountered to explain AI and healthcare: - Traditional algorithm-based systems rely on predefined actions and parameters conceived by engineers, whereas machine learning models are trained on massive datasets, capturing more edge cases and experiences than any one team could anticipate. It’s like a team of pilots writing a flight program based on their experiences versus a pilot who has flown on every flight ever taken. - While there’s ongoing debate about the importance of AI explainability, it's worth noting that humans often use tools without fully understanding how they work(e.g., bomb-sniffing dogs). What's critical is ensuring the accuracy of the tool and maintaining a human in the loop to interpret and act on the information provided. Healthcare is a complex system with various parts—genetics, research, environment, behavior—often functioning in isolation. New technologies & systems including AI allow us to connect these pieces, enabling information flow and informed decision-making that can finally deliver true patient-centered precision medicine. #innovation #health #ai

Mount Sinai Health System Opens State-of-the-Art AI Research Center : #news - Mount Sinai Health System has inaugurated the Hamilton and Amabel James Center for Artificial Intelligence and Human Health, a $100 million facility located in New York City’s Upper East Side, consolidates Mount Sinai’s various AI programs into a unified hub for research, development, and clinical application, marking a significant milestone in AI-driven healthcare innovation. Core Mission and Focus Areas The center aims to revolutionize healthcare by integrating artificial intelligence into key areas such as genomics, imaging, pathology, electronic health records (EHRs), and clinical care. By doing so, Mount Sinai seeks to bridge the gap between cutting-edge AI technology and practical applications that enhance patient outcomes. MEDPULSE AI Read More ▶️ https://buff.ly/3VbVDo6 💡 #aiinhealthcare #mountsinaihealth #MedPulseAI #AIinHealthcare #AIinMedicine

📈🔍 𝐀𝐈 𝐢𝐧 𝐑𝐚𝐝𝐢𝐨𝐥𝐨𝐠𝐲: Revolutionizing Diagnosis! 🌟 - 🧠 Smarter Insights: AI-driven image analysis enhances diagnostic accuracy, reducing human error and improving patient outcomes. 📊💡 - ⏱️ Time-Saver: AI algorithms rapidly process images, slashing wait times and prioritizing urgent cases for speedy intervention. 🚀⏰ - 🤝 Collaborative Power: AI complements radiologists, handling routine tasks and allowing experts to focus on complex cases requiring human insight. 🤝🩺 - 🔄 Continuous Learning: With every scan, AI improves, leveraging vast datasets to adapt swiftly to emerging patterns and diseases. 🔄📚 🔗 Dive deeper into the latest research with Sciqst! Generate comprehensive biomedical literature reviews effortlessly at sciqst.com 🧑🔬📝 #AIinRadiology #MedicalInnovation #HealthTech #FutureOfMedicine

Artificial Intelligence and Automation Trend:AI in Healthcare Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostic accuracy, predicting patient outcomes, and personalizing treatment plans. Recent advancements in machine learning and deep learning are enabling AI systems to process vast amounts of medical data quickly and accurately. Impact on the Industry: - Improved diagnostic tools and early detection of diseases. - Enhanced patient care with personalized treatment plans. - Streamlined administrative tasks, reducing costs and improving efficiency. Example: Google Health’s AI model can detect breast cancer with greater accuracy than human radiologists, showcasing the potential for AI to transform diagnostic procedures. Actionable Insight: Healthcare providers should explore partnerships with AI technology firms to integrate AI-powered diagnostic tools into their practice, ensuring they stay ahead of the curve in medical innovation. --- #TechyTuesday #ITMBusinessSchool #ESMEducation #peterdrucker2024 #PK2024

📊 AI Insights: Part 2 of Today's arXiv Highlights. This one is in the medical field. 🏥 Can AI revolutionize early sepsis detection and save lives? Exciting news! Researchers have developed 'SepsisLab', an innovative AI system for early sepsis prediction with groundbreaking features: Created by a team of medical and AI experts, SepsisLab introduces: ✅ Uncertainty quantification for predictions, especially crucial in early admission hours ✅ Active sensing algorithm to recommend the most informative variables for observation ✅ Robust performance on both public (MIMIC-III, AmsterdamUMCdb) and proprietary datasets ✅ Implementation as a practical system for clinical use This advancement could significantly improve sepsis diagnosis and patient outcomes, addressing a leading cause of in-hospital mortality. What are your thoughts on AI's role in critical care medicine? Share your views! Read more: https://lnkd.in/eMtHzvTB #Healthcare #ArtificialIntelligence #MedicalAI #PatientCare

Not enough people talk about these incredible tools for AI in healthcare. Don’t miss out: 1. 𝗜𝗕𝗠 𝗪𝗮𝘁𝘀𝗼𝗻 𝗛𝗲𝗮𝗹𝘁𝗵 - Simplifies data analysis by harnessing the power of AI to process vast amounts of medical literature and patient data, helping clinicians make informed decisions quickly. 2. 𝗭𝗲𝗯𝗿𝗮 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗩𝗶𝘀𝗶𝗼𝗻 - A game-changer in radiology, this tool uses deep learning algorithms to detect diseases in medical imaging, enabling faster diagnoses and reducing the burden on radiologists. 3. 𝗔𝗶𝗱𝗼𝗰 - Stands out with its real-time AI-powered radiology solutions that flag critical conditions, allowing for immediate action and intervention—crucial in emergency medicine. 4. 𝗧𝗲𝗺𝗽𝘂𝘀 - Boosts efficiency by integrating clinical and molecular data to tailor cancer treatment plans. This personalized approach improves patient outcomes and streamlines treatment processes. 5. 𝗗𝗲𝗲𝗽𝗠𝗶𝗻𝗱 𝗛𝗲𝗮𝗹𝘁𝗵 – I recommend it to everyone for its groundbreaking work in AI-based predictive analytics, which helps healthcare providers anticipate patient needs and reduce hospital readmissions. Discover how these tools can transform your healthcare practices and improve patient care. The future of medicine is here, and it's powered by AI! #HealthcareAI #DigitalHealth #MedicalInnovation #PatientCare #HealthTech #ArtificialIntelligence

📚 𝐄𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐔𝐩𝐝𝐚𝐭𝐞 𝐂𝐨𝐦𝐢𝐧𝐠 𝐒𝐨𝐨𝐧! 🏥 I’m pleased to share that I’ve been working on a cutting-edge research project titled “𝐃𝐢𝐚𝐠𝐧𝐨𝐬𝐢𝐬 𝐚𝐧𝐝 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐆𝐥𝐚𝐮𝐜𝐨𝐦𝐚 𝐔𝐬𝐢𝐧𝐠 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬.” Glaucoma, a leading cause of vision loss, demands early and accurate diagnosis. My research focuses on developing a machine learning framework that not only predicts glaucoma but also provides transparent, interpretable insights into the diagnosis process. By integrating clinical data like fundus images, retinal nerve fiber layer tests, and intraocular pressure measurements, we aim to improve glaucoma detection. In this project, we are utilizing advanced machine learning models like 𝗡𝗮𝗶𝘃𝗲 𝗕𝗮𝘆𝗲𝘀, 𝗥𝗮𝗻𝗱𝗼𝗺 𝗙𝗼𝗿𝗲𝘀𝘁, 𝗮𝗻𝗱 𝗟𝗶𝗴𝗵𝘁𝗚𝗕𝗠, ensuring both precision and explainability in diagnosis. I’ll be sharing the full research soon and can’t wait to contribute to the exciting developments in AI-driven healthcare! #AI #MachineLearning #Healthcare #Glaucoma #ExplainableAI #LightGBM #RandomForest #MedicalResearch #DataScience #Innovation

NIH Workshop: AI with Medical Imaging. Mar. 11-12. It's FREE, but you must Register. This public planning forum will cover a variety of topics, and ethics is part of the Agenda. The goal is more personalized medicine, aka Precision Medicine, using multiple types of patient data. Follow the links to view topics and speakers.