Abstractive Health has launched a new training tool, Clinical Time Machine, designed to help doctors sharpen diagnostic skills using real, historical patient records. The simulation is available now through the company’s platform at no cost. Built on HIPAA-compliant AI systems, it immerses clinicians in centuries-old clinical cases. CEO Vince Hartman describes it as a “Flight Simulator for medicine.” With very few doctors exposed to AI-generated full medical record summaries, the goal is to change that quickly. The platform allows doctors to explore rare or complex cases in a no-risk setting, encouraging hands-on AI engagement.
Abstractive Health Turns Medical History Into an AI-Powered Learning Experience
Clinical Time Machine uses authentic handwritten patient records, many dating back hundreds of years. These are transformed into readable summaries using AI-powered tools developed by Abstractive Health. The tool builds on the same technology currently used in hospital settings to summarize live electronic health records. Clinicians navigate the simulated case much like they would a real one—reviewing histories, lab results, and even receiving time-based clinical updates.
“It’s not a quiz,” Hartman explains. “It’s about engaging clinical reasoning in a sandbox where doctors can make decisions and learn.” The system does not require integration with existing EHRs, which removes a major barrier to adoption. Instead, the experience is immediate and interactive, encouraging exploration and curiosity. The company hopes it will help clinicians connect better with AI by putting it in their hands.
Early Feedback Fuels Momentum for Abstractive Health’s Clinical AI Simulation
Clinical Time Machine is already being piloted at Weill Cornell Medicine, where researchers are using the platform to improve handoff notes in Emergency Medicine. In Canada, a rollout is underway through a partnership with WELL Health Technologies. That deal followed an investment agreement signed last year. Abstractive Health’s underlying summarization engine uses advanced OCR and retrieval-augmented generation to convert even difficult-to-read handwritten notes into coherent narratives.
But challenges remain. Adoption of AI in clinical workflows is still slow; fewer than 1% of doctors have ever used an AI tool to read full medical records, according to Hartman. Many clinicians are wary of trusting AI with anything beyond administrative tasks. Still, early reactions from test users have been positive, especially regarding the historical depth and diagnostic freedom the simulation offers. There is growing interest in tools that teach reasoning, not just speed.
AI Launch Signals Shift Toward Hands-On Learning in Medicine
Clinical Time Machine marks a shift in how AI is introduced to the medical field, not just as a tool to save time, but as a way to elevate thinking. By focusing on curiosity and decision-making, Abstractive Health hopes to foster deeper clinical understanding. It’s work with Weill Cornell and WELL Health shows early traction, but broader adoption will depend on continued ease of use and visible impact. As Hartman puts it, “This isn’t about replacing doctors, it’s about helping them think better.” With more cases in development and open access for now, the Clinical Time Machine could become a new standard for AI-driven medical training.
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