π§ Evaluating Clinical AI with OpenAI's HealthBench, π₯ Advancing Healthcare Through Global AI Collaborations, π GPT-4oβs Role in Interprofessional Medical Education, and More! π
Updates on Artificial Intelligence & Emerging Technologies in Medicine π€π
Welcome to The βMed AIβ Capsule Newsletterβyour go-to source for exploring how AI and emerging technologies are transforming medicine! Whether you're a medical professional π©ββοΈ, a tech enthusiast π», or simply curious π§ , The 'Med AI' Capsule is for you! Stay ahead of the curve with the latest trends, insights, and updates in the rapidly evolving world of AI and emerging technologies in medicine. π
In todayβs capsule:
4 News Updates
3 Research Papers
2 Learning Resources
1 Worth-Attending Event, and more!
Time to Read: Around 7 to 10 minutes.
Exciting News! You can now enjoy this newsletter issue in a new, accessible format. Click below to listen to the podcast version and dive deeper into the latest insights and stories while on the move!
π° News Updates
π§ͺ OpenAI Launches HealthBench to Benchmark AI in Clinical Scenarios

As medical AI tools proliferate, OpenAI has released HealthBench, an open-source framework designed to evaluate how large language models (LLMs) perform in realistic clinical conversationsβnot just multiple-choice tests.
Built with 262 physicians across 60 countries, featuring 5,000 multi-turn scenarios and 48,562 rubric criteria.
Focuses on real-world themes: emergency care, uncertainty, global health, tailored communication, and more.
Shifts away from multiple-choice examsβtests decision-making, depth, and reliability in messy contexts.
o3 model scores ~60%, doubling GPTβ4o and far surpassing GPTβ3.5 (~16%). Small models like GPTβ4.1 nano also excel.
Includes HealthBench Hard, a challenging subset where top scores drop to ~32%.
Benchmarks are open-source, with data and code available for public use and improvement.
Praised for transparency and clinical relevance, but experts urge caution: grading bias and subgroup disparities still need attention.
βHealthBench tests how well AI models perform in realistic health scenarios, based on what physician experts say matters most.β
- Authors
Why It Matters: HealthBench raises the bar for evaluating clinical AIβoffering transparency, physician-driven scoring, and an open framework for ongoing development. As more health systems begin deploying LLMs, tools like this are crucial for aligning model capabilities with frontline realities.
π Other Highlights
Microsoft unveils an agentic AI orchestrator for cancer care, integrating multimodal agents into clinical workflows to streamline tumor board reviews and enable precision medicine.
IIT Delhi and AIIMS launch a βΉ330 crore Centre of Excellence to develop scalable, AI-driven healthcare solutions targeting national health priorities like cancer, TB, and rural diagnostics.
Oracle Health, Cleveland Clinic, and UAEβs G42 partner to build a global AI health platform enabling real-time, point-of-care insights and nation-scale analytics across the U.S. and UAE.
β¨ Industry Spotlight*

CARPL.ai is building a vendor-neutral platform that helps hospitals deploy and monitor radiology AI tools at scale. With over 175 apps from 75+ vendors, their FDA-cleared system integrates directly into existing PACS and RIS workflowsβno extra hassle for clinicians.
The platform offers a full suite for AI lifecycle management, from pre-deployment validation to real-time monitoring. Hospitals can test models on their own imaging data, track performance across demographics and devices, and get alerts for bias or model drift.
Already live in the U.S., Brazil, Singapore, and India, CARPL is improving diagnostic speed and accuracy in real-world settings. Their $6M seed funding and partnerships with top imaging players show serious momentum in streamlining AI adoption for radiology teams.
*This editionβs βIndustry Spotlightβ is editor-picked, not sponsored.
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π¬ Latest Research Papers
π GPT-4o with Iterative Refinement Outperforms Clinical Mentors in InterProfessional Education (IPE) Scenario Design
GPT-4o with iterative refinement produced IPE scenarios faster and of higher quality than clinical mentors.
Scenarios scored better in challenge and student engagement; standard prompts lagged behind.
Cases took 9 minutes to generate vs. 118 minutes for human-crafted ones.
Blinded reviewers couldnβt distinguish refined AI scenarios from human-written ones.
The iterative method mimics real clinical case development using multi-role feedback loops.
βThis approach not only showcases the substantial potential of AI in creating personalized learning materials but also presents an innovative and effective solution to the current challenges in IPE.β
- Authors
Why It Matters: Faculty shortages and scheduling conflicts often hinder IPE implementationβespecially in resource-limited settings. This study highlights a scalable, AI-assisted approach to scenario design that maintains high educational quality while reducing reliance on interprofessional faculty.
π Other Highlights
Patients view AI-CDSS as potentially supportive but raise concerns about trust, responsibility, and self-determination, emphasizing the need for transparency, human oversight, and shared decision-making.
AI assistance significantly improves endoscopistsβ sensitivity and accuracy in detecting superficial esophageal squamous cell carcinoma, benefiting both experts and non-experts in video-based evaluations.
β Knowledge Quiz
Mark your answer and think about it as you read through the remaining newsletter, and find the correct answer at the end!
π Learning Resources
Your feedback is crucial to me, as it helps me understand your interests and improve my offerings. I would appreciate it if you could take a few minutes to share your thoughts about what you've enjoyed and what you think I could do better.
Exciting Announcement
π§βπ» Worth-Attending Event
Letβs wrap it up with a thought-provoking quote! π‘
βAI has allowed me, as a physician, to be 100% present for my patients.β - Michelle Thompson, DO, family medicine specialist
Stay tuned for the upcoming issues of my newsletter to explore the latest breakthroughs and dive deep into the transformative power of artificial intelligence and emerging technologies, shaping a healthier future. π
Disclaimer: The content in this newsletter was partly curated and summarized using AI LLMs, which can make mistakes. Please check all important information. For any issues or inaccuracies, please reach out at avneeshkhareonline@gmail.com.
Just came across your newsletter - super useful, thank you!
I am very happy to come across this. As a Healthcare student, this newsletter becomes a comprehensive, updated reading resource on Artificial Intelligence in Healthcare, for me to explore further.