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AIHealthTech Insider: Issue # 34

In this issue, we look at how NVIDIA's MONAI Deploy is changing medical imaging by working with Siemens Healthineers. We also explore new ideas from HIMSS25, see how AI helps treat UTIs, talk about Rad AI's funding, and discuss more ways AI is affecting healthcare.

NVIDIA MONAI Deploy Transforms AI in Medical Imaging

NVIDIA’s MONAI Deploy is now integrated into Siemens Healthineers’ Syngo Carbon and syngo.via platforms, streamlining AI deployment in clinical imaging. This collaboration, announced at RSNA 2024, allows researchers and healthcare providers to integrate AI into medical workflows faster—reducing deployment time from months to just a few clicks.

Why It Matters:

• Faster AI Adoption – MONAI Deploy simplifies the transition from AI research to real-world clinical use.

• Seamless Integration – AI applications can be quickly deployed on the Siemens Healthineers Digital Marketplace.

• Cutting-Edge AI Models – MONAI v1.4 introduces MAISI, a diffusion-based AI model for generating CT scans, and VISTA-3D, a segmentation model for over 120 organ classes.

With 3.5 million downloads and adoption across top research institutions, MONAI is shaping the future of AI-powered medical imaging—from hospitals to startups and beyond.

👉 Read the full story on Nvidia Blog

HIMSS25: A Gateway to Healthcare Innovation

This year’s HIMSS25 event is bringing an exciting array of new features designed to empower attendees with the latest tools, trends, and strategies. From cutting-edge digital health solutions to immersive experiences in AI, interoperability, and smart health, the event will showcase breakthroughs shaping the future of care delivery. HIMSS25 is set to redefine the landscape of healthcare technology and innovation.

Key Highlights:

• Addressing Health Inequities: The Trustworthy Responsible AI Network (TRAIN) focuses on ensuring rural and underserved communities are part of the AI revolution by establishing guardrails for responsible AI in healthcare.

• Modernized EHRs: Upgraded electronic health record systems and standardized data exchange are essential for equitable AI adoption.

• Local Validation Matters: AI tools must be tested on locally validated, representative data to avoid worsening outcomes for medically complex patients in rural areas.

• Building Trust: Governance, lifecycle management, and trust-building are critical to ensuring AI benefits all communities equally.

• Call to Action: Healthcare leaders must ensure underserved communities have the tools and resources to innovate alongside urban and affluent areas.

Must-Attend Sessions:

“From Academic Medical Centers to Rural Healthcare: Operationalizing Responsible AI”
Jennifer Stoll of OCHIN will provide actionable insights into deploying responsible AI to benefit rural health systems and medically underserved communities. Attendees will gain practical takeaways on building trust, improving data governance, and fostering equitable innovation.

The Future of Imaging: AI in Outpatient Radiology and MRIs” Dr. John Simon, CEO of SimonMed Imaging, will share insights into how AI is transforming outpatient radiology. His session will explore the benefits of AI in improving imaging accuracy, speeding up patient care, reducing costs, and alleviating radiologist burnout. With over 30 years of experience, Dr. Simon brings unmatched expertise in radiology and will highlight future technological advancements shaping medical imaging.

👉 Don’t miss this opportunity to explore how responsible AI is shaping the future of healthcare and creating sustainable solutions for every community.

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AI-Powered Decision Support Optimizes UTI Antibiotic Prescriptions

An AI-driven tool, UTI Smart-Set (UTIS), is revolutionizing UTI treatment by reducing antibiotic mismatches and improving prescription accuracy. Using machine learning to predict resistance patterns, UTIS personalizes antibiotic recommendations based on patient history and clinical guidelines.

A study of 171,010 UTI cases showed:

• 📉 37.4% reduction in antibiotic mismatches when UTIS recommendations were followed.

• 🚫 80.5% decrease in ciprofloxacin prescriptions, cutting unnecessary broad-spectrum antibiotic use.

• 👩‍⚕️ 55.6% lower mismatch rate in women over 50, improving treatment precision.

• ⚡ Faster decision-making with AI-backed real-time recommendations integrated into clinical workflows.

By embedding AI into electronic health records, UTIS supports data-driven prescribing, helping fight antimicrobial resistance while improving patient care.

👉 Read the full story on Nature

GTC 2025: #1 AI Conference

The GTC 2025 (GPU Technology Conference) by NVIDIA, from March 16-21, 2025, in San Jose, California, will focus on AI in healthcare. It will feature over 900 sessions, including keynotes, technical training, and workshops.

Highlights include GE Healthcare's AI-powered portable ultrasound devices and the convergence of quantum computing, AI, IoT, and real-world data (RWD), showcasing AI-driven analytics transforming healthcare.

Rad AI Secures $60M Series C to Expand Generative AI in Healthcare

Rad AI, a leader in generative AI for radiology, has raised a $60M Series C funding round led by Transformation Capital, bringing its total funding to $140M and valuing the company at $525M. This funding will accelerate the development and deployment of AI-driven solutions that enhance radiologist efficiency and reduce burnout.

Why It Matters:

• Radiologist Efficiency – AI-powered Rad AI Reporting cuts dictated words by 90%, saving up to 50% of time per report.

• Burnout Reduction – With 88.4% of radiologists feeling overworked, AI-driven automation lightens workloads.

• Enhanced Patient Care – Rad AI Continuity improves follow-up rates for potential cancers from 30% to over 75%, ensuring timely diagnoses.

• Industry-Wide Impact – Used in health systems covering nearly 50% of U.S. medical imaging, with adoption growing rapidly.

Rad AI continues to drive AI-powered transformation in radiology, ensuring faster, more accurate diagnoses while revolutionizing healthcare workflows.

👉 Learn more from Rad AI

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