EarlySign and Geisinger partner on AI-based detection of disease risk

11 July 2019 (Last Updated December 23rd, 2019 10:22)

Medial EarlySign has partnered with Geisinger and its Steele Institute for Health Innovation to develop new machine learning-based solutions for the identification of people at risk of chronic and high-burden diseases.

EarlySign and Geisinger partner on AI-based detection of disease risk
Geisinger and EarlySign will leverage AI technology to detect acute and chronic diseases. Credit: Gerd Altmann from Pixabay.

Medial EarlySign has partnered with Geisinger and its Steele Institute for Health Innovation to develop new machine learning-based solutions for the identification of people at risk of chronic and high-burden diseases.

EarlySign develops artificial intelligence (AI) solutions aimed at detecting and preventing diseases early.

As part of the latest multi-year alliance, the company’s advanced software solution called LGI-Flag will be deployed for the detection of individuals at risk of significant lower GI disorders.

LGI-Flag is designed to analyse medical data such as changes in routine blood tests in order to identify patients who will benefit from further assessment.

Geisinger and EarlySign will leverage the technology for similar application in other acute and chronic diseases. Geisinger will contribute to the alliance via its innovation infrastructure, data assets and care teams.

Geisinger associate chief quality officer Keith Boell said: “EarlySign’s technology and the LGI-Flag solution will potentially assist our teams to more quickly identify significant lower GI disorders and intervene earlier than we historically have been able to.

“We look forward to advancing our use of this technology while leveraging our experience to help more patients benefit from these life-changing medical advances.”

EarlySign’s LGI-Flag solution has been in use since 2015. Healthcare systems worldwide leverage LGI-Flag to identify patients at risk for lower GI disorders that are related to chronic occult bleeding.

Medial EarlySign co-founder and CEO Ori Geva said: “This is the first step of our ultimate goal: enabling healthcare systems to identify and connect with those high-risk patients and engage with them early enough via interventions that may prevent or delay disease progression.”

In May, EarlySign unveiled new predictive risk solutions called AlgoMarkers for the identification of patients at high risk for diabetes and downstream complications.