NVIDIA Healthcare reposted this
There are now more than 1,000 functions supporting gpuArray on MATLAB, making it easier than ever to accelerate your #HPC workflows. Learn how you can boost performance with minimal code changes. ➡️ https://nvda.ws/4gOfbI8 MathWorks
Learn how developers in the fields of image-guided #surgery and surgical vision tackle challenges in creating systems and applications that can significantly improve surgical workflows. #AI #healthcare #medicaldevices https://nvda.ws/3Yg3JxC
Join tomorrow’s discussion to explore how #AI and #digitalbiology data are transforming global #healthcare. Learn about the critical factors driving innovation, the role of public & private investment, and how to maintain US leadership in AI for healthcare and biology. #DCAISummit Register now ➡️ https://lnkd.in/giN564Hb 🗓️ Tuesday, Oct 8 | 3:00 PM - 3:40 PM EDT
🌟 Discover how AI-powered #ZeroShotLearning is accelerating treatments for rare diseases by identifying existing drugs in record time. 🧬 💊 #AI #DrugRepurposing #HealthcareInnovation Read the full story ➡️ https://nvda.ws/3N9o4P4
From Genetic Engineering & Biotechnology News, NVIDIA's latest #AI tool, the NIM Agent Blueprint, is set to change the game for drug developers. By using #generativeAI, it enhances virtual screening and molecule design, making #drugdiscovery faster and more efficient. #NIM #healthcare https://nvda.ws/3zDFIHt
Join our on-demand webinar to explore how spatial omics is revolutionizing cancer care! Learn about the latest advancements in biomarkers, targeted therapies, and personalized medicine. Discover the power of spatial transcriptomics in understanding the complex mechanisms of cancer with our experts Mitsuho Imai-Sumida, MD PhD Woong-Yang Park Adrian Benjamin Harry Clifford. Register now! #drugdiscovery https://nvda.ws/3TIBk0C
Montai Therapeutics is leveraging NVIDIA's BioNeMo DiffDock NIM to develop an advanced multimodal #AI #drugdiscovery platform, incorporating a library of Anthromolecule chemistry. This approach has led to the creation of a highly accurate and efficient model, capable of generating 40 poses per ligand using 8xA100 GPUs, with a processing speed of 0.76 seconds per ligand. #healthcare Read more on our latest technical blog. https://nvda.ws/4eEru85
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Leading U.S. medical professionals - John Garrett, Khaled Younis, PhD, Yuankai Huo Mayo Clinic Case Western Reserve University Georgetown University Medical Center UC San Diego School of Medicine University of Florida College of Medicine Vanderbilt University Medical Center UW School of Medicine and Public Health MedAiConsult LLC Society for Imaging Informatics in Medicine (SIIM) - transforming tumor segmentation through #federatedlearning. Discover the transformative effects of NVIDIA Flare and AI-assisted annotation collaboration with Flywheel.io! #healthcare #GenerativeAI #MONAI https://nvda.ws/3Zw5fNa
Building advanced AI teams and solutions. CTO, genAI.
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