Atropos Health Deploys AI Models to Identify Undiagnosed Conditions

Atropos Health announced on Monday the deployment of AI models to identify patients living with undiagnosed conditions. These AI models will be made available to clinicians through members of the Atropos Evidence Network. According to the company, Atropos Health’s AI-built models are developed, trained, and tested using real-world data (RWD) from the Atropos Evidence Network, which includes over 300 million patient records. The goal is to reduce the time from initial symptoms to testing, diagnosis, and treatment at the point of care.

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Developed by Experts, Powered by Real-World Data

The models are created by Atropos Health medical doctors, epidemiologists, statisticians, and experts. Their implementation is expected to save clinicians time and improve the patient experience by enabling earlier identification of conditions and faster treatment, the company said.

“Increasing the speed, inclusivity and accuracy of precision medicine is the power of Generative AI in practice,” said Brigham Hyde, CEO and co-founder at Atropos Health. “By utilizing the portfolio of Atropos Health services such as Geneva OS and the Atropos Evidence Network, precision medicine based on RWE is becoming a reality and reducing the time from symptom to treatment leads to better outcomes for patients and better experiences for providers.”

Role of the Atropos Evidence Network

Atropos Health noted that members of the Atropos Evidence Network can access more RWD tailored to their specific needs, supported by the Real World Fitness Score (RWFS), which evaluates the relevance and quality of data for individual inquiries. These additional datasets enhance opportunities for partners to identify “fit-for-purpose” data.