Healthcare
Case StudyAnthem

Anthem aims to predict the occurrence of allergies using machine learning

Anthem has partnered with Doc.ai to execute a 12-month trial to analyse how allergies affect people. The system is based on AI and machine learning algorithms to identify predictive models and identify patterns and on blockchain to ensure the privacy and anonymity of medical data.

Context

"Allergies plague more than 50 million Americans with symptoms each year; over 40 percent of children have allergies and over 30 percent of adults also suffer. Although symptoms may range from itchy eyes, sneeze and runny noses, food allergies can be critical and lead to hospitalization – leading to approximately 200,000 emergency room visits a year. It is estimated, by WebMD Medical Reference, that allergies cost the U.S. healthcare system $18 billion annually."

The Project

"To better understand how allergies affect people and the patterns that arise, Anthem and Doc.ai are putting together a 12-month trial using AI and machine learning algorithms to identify predictive models for allergies. To do this, Doc.ai’s advisors from Harvard will take health data from sample groups based on phenome (such as height, weight and age), exposome (environmental effects such as weather and pollution based on location), and physiome (such as physical activity, daily steps and diet). This data will be correlated in a massive database collected from trial subjects in an effort to build a pool of historical information that can be mined for patterns that would connect back to locations, behaviors and certain health factors that would give a better picture of when allergies are triggered and who they affect. By partnering with Anthem, a company that affiliates with the Blue Cross and Blue Shield healthcare insurance federation, participants for this trial could be opted-in at the scale needed. Most importantly, he [Walter De Brouwer, co-founder of Doc.ai.] added, this technology will “enable individuals to collect and own their health data while empowering data scientists using deep learning to collaborate with consumers, doctors and researchers to find personalized healthcare solutions."."

AI Usage

"AI and machine learning algorithms to identify predictive models for allergies."

Data

health data from sample groups based on phenome (such as height, weight and age), exposome (environmental effects such as weather and pollution based on location), and physiome (such as physical activity, daily steps and diet).

Results

Proof of concept; results not yet available

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