Bloom Value Corporation

Moumita Dhar

Arun Hampapur

Sharathchandra Umapathirao Pankanti

Sampoorna Hegde

Roona Shree

Venu M Kondle

Yashpal Gulab Dhawle

Priyanka Rajesh

A system and method to authorize requests for procedures or medical claim requests is described. In one aspect, datasets from multiple data sources, including historical authorizations associated with various medical claims, are processed. The machine learning engines and the machine learning models are trained based on the received data. Simultaneously, real-time authorization requests are received and analyzed from secondary data sources. Each request is split into service requests based on second attributes, which include identifiers linked to services. The services are encoded using fixed-length encoding, and unique numeric identifiers are assigned to categorical variables. For each encoded service request, contexts, actions, and decisions are determined by comparing the first attributes of historical authorization requests with the second attributes of real-time requests. Service requests are then categorized into cohorts based on similarity metrics between their second attributes and those of historical authorizations. This comparison enables efficient processing and informed decision-making.

Intelligent authorization system

Growing community of inventors

Bengaluru, India

Moumita Dhar