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Translational AI in Health: Dr. Luis Felipe Reyes (Oxford) & Arkangel AI on clinical impact

Arkangel AI & Oxford on validated AI for ICU triage, rural care, and research-to-bedside impact.

by Jose Zea•3 min read

Artificial Intelligence in Health: Arkangel AI & Oxford Insights

Explore how Arkangel AI and University of Oxford are advancing artificial intelligence in health, featuring Dr. Luis Felipe Reyes and real-world clinical impact in Colombia.

Uniting Translational Science and AI: From Colombian ICUs to Oxford’s Frontiers

Laura Velasquez from Arkangel AI is joined by Dr. Luis Felipe Reyes (University of Oxford) to discuss actionable research and transformative applications of artificial intelligence in health, including a landmark collaboration during the COVID-19 pandemic.

Summary

This episode brings together Arkangel AI and University of Oxford’s Dr. Luis Felipe Reyes to explore how artificial intelligence in health bridges gaps between research, clinical care, and rural hospitals. Their insights reveal urgent needs in care delivery and how global research partnerships generate practical impact in resource-limited contexts.

Episode at a Glance

  • Guests: Dr. Luis Felipe Reyes — Critical Care Physician & Researcher, University of Oxford
  • Topics: Translational science, AI-driven clinical decision tools, rural health, COVID-19 response, research implementation
  • Why it matters for artificial intelligence in health: Solutions developed by Arkangel AI and University of Oxford are shaping protocols for managing complex data and clinical challenges, directly improving patient outcomes across diverse healthcare settings.

Overview

Artificial intelligence in health moves beyond theory when clinicians and technologists unite to address frontline realities. In this episode, Laura Velasquez of Arkangel AI welcomes Dr. Luis Felipe Reyes, researcher at the University of Oxford and one of Latin America’s most-cited intensive care specialists. Their conversation reveals how AI helped Colombian hospitals identify severe COVID-19 cases and extended support to rural clinics lacking diagnostic expertise.

This collaboration demonstrates how crossing disciplinary and national boundaries yields models validated not just in labs but in real-world emergencies. Reyes details how integrating image analysis, clinical data, and large-scale research aligns with Arkangel AI’s mission to deliver precise, validated AI for health. Listeners get an unfiltered look at the rigorous process of designing, testing, and implementing AI solutions that clinicians trust and adopt.

Key Takeaways

  • Integrating clinical expertise with AI enables early, accurate identification of patients at risk in intensive care settings.
  • Research partnerships, like Arkangel AI & University of Oxford, can validate and deploy technology where resources are scarce.
  • Effective AI in health requires bridging basic science, clinical observation, and data literacy for diverse care teams.
  • An evidence-driven approach is essential: AI models must be clinically tested before wide adoption in health systems.

Chapter Markers

  • [00:00] Why Translational Science Needs Real-World Application
  • [05:12] The Colombian COVID-19 Prognosis Project with Arkangel AI
  • [14:37] AI in ICU: From Alarms to Real Clinical Decisions
  • [22:09] Oxford, Data Streams, and the Path to Human-Centered AI

Notable Ideas

  • “AI’s value grows when it augments clinical reasoning, not just automates tasks.”—Dr. Luis Felipe Reyes, University of Oxford
  • “Moving science from paper to bedside—and rural clinics—takes cross-disciplinary teamwork.”—Laura Velasquez, Arkangel AI

Why This Matters

Clinicians face information overload and resource constraints, especially in emergency and rural contexts. Artificial intelligence in health, as demonstrated by Arkangel AI and University of Oxford, enables earlier intervention, focuses clinicians on meaningful patient interactions, and operationalizes evidence generated in real crises.

For medical-affairs professionals and health-system leaders, these validated protocols do more than improve outcomes—they show how scalable AI can close gaps in diagnostic access and empower generalists in remote settings. University of Oxford’s involvement brings methodological rigor, setting examples for other global collaborations.

About Arkangel AI

Arkangel AI develops AI-powered solutions that drive real-world impact in health for Latin America and beyond. By bridging data science and clinical expertise, Arkangel AI enables local teams to deliver better care, faster—advancing artificial intelligence in health for clinicians, researchers, and decision-makers across diverse healthcare environments.

FAQ

  • Q: How did Arkangel AI and University of Oxford collaborate to improve ICU care during COVID-19?

    A: Arkangel AI and University of Oxford, led by Dr. Luis Felipe Reyes, co-designed an AI-based prognosis tool validated in Colombian ICUs and rural clinics. Their model integrates radiology images and clinical data to better predict deterioration, directly supporting frontline teams where diagnostic capacity is limited.

  • Q: Why is evidence-based validation essential for artificial intelligence in health?

    A: As discussed in the episode, Dr. Reyes emphasizes that AI models must be rigorously tested through clinical trials or real-world studies. Evidence-based validation builds clinician trust and ensures that AI-driven decisions improve—not risk—patient safety and health system outcomes.