Abstractive Health has introduced an AI-driven simulation known as Clinical Time Machine, designed to enhance diagnostic training for physicians.
Currently accessible via Abstractive Health’s platform, the clinical solution allows medical professionals to engage with real historical medical cases, providing a risk-free environment for exploring rare and complex conditions.
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Developed on a HIPAA-compliant platform that also facilitates the real-time summarisation of electronic health records (EHRs) in hospitals, Clinical Time Machine allows clinicians to delve into diagnostic cases from the past.
The solution does not require any direct EHR integration.
Abstractive Health CEO Vince Hartman said: “Three years after ChatGPT, fewer than 1% of physicians have ever seen an AI full medical record summary. We’re changing that.”
Each simulation begins with an AI-generated summary of original medical documents, some dating back hundreds of years.
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By GlobalDataClinicians navigate through a structured chart, examining everything from the history of the current illness to laboratory results and vital signs.
They obtain simulated updates that reflect clinical observations made at the time.
Hartman added: “It’s not a quiz. It’s about engaging clinical reasoning in a sandbox where doctors can make decisions and learn from them.”
The technology behind Clinical Time Machine is based on Abstractive Health’s summarisation, retrieval-augmented generation (RAG), and agentic AI platform.
It utilises advanced optical character recognition (OCR) and an AI summarisation pipeline capable of transforming handwritten notes into coherent clinical narratives.
Currently, the summarisation solution is being trialled at Weill Cornell Medicine in a research partnership aimed at improving Emergency Medicine handoff notes.
Furthermore, Abstractive Health is set to expand the simulation’s reach to outpatient clinics in Canada through a collaboration with WELL Health Technologies, which was established after an investment and distribution agreement last year.
