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Trustwise and Partners Develop MedAssist GPT: AI-Powered Medical Education Platform

by Syed Hamza Sohail 11/26/2024 Leave a Comment

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What You Should Know:

– Trustwise, an innovator in AI performance and risk management, has collaborated with Health Innovation Kent Surrey Sussex (Health Innovation KSS), Hitachi Digital Services, and Further to co-develop MedAssist GPT, a generative AI application for medical education that leverages NVIDIA NIM microservices. 

– The application equips UK medical students with real-time, personalized evidence-based clinical guidance. Integrating more than 700 National Institute for Health and Care Excellence (NICE) guidelines and NHS Formulary data, MedAssist GPT covers over 30,000 medicines, offering unparalleled resources for clinical learning.

MedAssist GPT: Revolutionizing Healthcare Training with AI Safety, Speed, and Sustainability

MedAssist GPT, hosted on the Google Cloud Platform and powered by NVIDIA NIM, leverages the Writer Palmyra-Med large language model (LLM) to transform healthcare training. Designed to enable UK medical students to engage in clinical scenario simulations, practice safe and cost-effective prescribing, and receive real-time feedback, MedAssist GPT supports over a dozen languages and adheres strictly to national healthcare standards.

Innovative AI for Healthcare Training

MedAssist GPT prioritizes safety, personalization, and sustainability:

  • Enhanced Safety and Reliability: Developers addressed challenges such as AI output alignment, data privacy, and hallucinations to deliver evidence-based medical guidance tailored to regional protocols. The tool is rigorously aligned with NICE guidelines, drug formulary data, and UK healthcare regulations.
  • Optimized Performance: Real-time guidance during clinical simulations was achieved through low-latency, high-throughput AI. NVIDIA AI Enterprise solutions minimized LLM token inefficiencies, ensuring cost-effective and scalable operations.
  • Sustainability Commitment: Adhering to NHS sustainability goals, MedAssist GPT reduces its carbon footprint, integrating environmentally responsible AI practices into its core design.

Collaboration Drives Innovation

MedAssist GPT is the product of collaboration among industry leaders, each bringing unique expertise:

  • Trustwise Optimize:ai provided a trust and optimization layer, enhancing safety, alignment, and operational efficiency by reducing token costs and latency.
  • NVIDIA AI Enterprise enabled high-speed inferencing and cross-platform scalability, ensuring seamless performance.
  • Writer’s Palmyra-Med LLM addressed the specific linguistic and knowledge needs of healthcare and life sciences.
  • Further refined conversational user experiences and optimized AI models for practical medical training applications.

Remarkable Outcomes and Future Goals

Early beta tests revealed significant advancements:

  • A 90% improvement in AI alignment with NICE guidelines, ensuring accurate medical recommendations.
  • A 30% reduction in response times, enhancing real-time feedback during simulations.
  • A 40% reduction in token costs and a 64% decrease in energy consumption and carbon emissions, supporting operational efficiency and sustainability.

Health Innovation KSS, part of the NHS England Health Innovation Network, plans to rigorously test and refine MedAssist GPT with students at the University of Surrey’s School of Medicine. This initiative aims to prepare the tool for full-scale rollout, equipping future healthcare professionals with AI-driven resources to enhance training and patient care outcomes.

Manoj Saxena, CEO and founder of Trustwise, highlighted the innovation’s impact: “MedAssist GPT sets a new standard for healthcare training, blending safety, speed, and sustainability. Collaboration among Trustwise, Health Innovation KSS, Hitachi Digital Services, and Further ensured the creation of a tool that empowers students with evidence-based insights while aligning with principles of trustworthy AI.”

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Tagged With: Artificial Intelligence, Generative AI

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