The largest and only model trained on patient medical events


140M

Patient Histories

350M

Parameters

63B

Tokens




What healthcare leaders are saying about GenHealth.ai










Explore generative AI use cases for healthcare



Generative Healthcare AI

GenHealth.ai is building AI for healthcare from the ground up. We are not simply applying off the shelf LLMs to healthcare, instead we have trained a state-of-the-art foundation model using a vocabulary native to healthcare and data from over 100M patients. Our Large Medical Model (LMM) beats the performance of all existing solutions on the market for healthcare risk and cost prediction.

Introducing the Large Medical Model (LMM)

Large Medical Model (LMM) vs Large Language Model (LLM)
GenHealth.ai has pioneered the Large Medical Model (LMM) for healthcare. Utilizing neural network transformers, our LMM is similar to Large Language Models (LLMs) but with a crucial difference: it doesn’t use natural language. Instead, it operates on a vocabulary of medical codes and events, like conditions, procedures, and medications. GenHealth's technology offers unmatched capabilities beyond the reach of LLMs. You can simulate patient futures, predict healthcare costs, and understand medical event liklihood over time with an accuracy that exceeds current approaches. Additionally, our model natively integrates with healthcare standards like FHIR, HL7, or X12, but also unstructured documents like PDFs.

Insights on generative AI for healthcare

Generative AI in Healthcare: The Definitive Guide
Healthcare Embeddings API
Generative AI vs Classical Statistics Healthcare Analytics
Learn about the bleeding edge of generative AI in healthcare with these foundational articles and more expert content from our Gen AI healthcare blog.

Deploying our medical model in healthcare apps

Automated Prior Authorization
Gen AI Healthcare Analytics
Our vision extends beyond foundation models for healthcare, we are reimagining healthcare by building applications natively on generative AI. Leveraging our Large Medical Model, we built applications that cut 90% of the administrative burden of prior authorizations, and a healthcare analytics chatbot that can answer any population health questions of the past, present, AND future.





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