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Our client needed data processing tools that would enable them to aggregate and index data from audio interviews of patients. They needed this for a knowledge graph that would include temporal markers of events preceding the onset of disease.
Arrayo provided engineering services to create a data processing solution for extracting a knowledge graph from audio interview transcription. This solution was created as a cloud-based platform comprised of the following components:
Arrayo developed Software components using Python and SQL to ensure seamless integration with standard libraries, document APIs, and custom code. To enable incorporation of custom parser capabilities, a standard RESTful API was delivered, accompanied with JSON schema specification and validation.
The system was delivered as a containerized application that was hosted on an AWS cloud environment. As part of the solution, services to support continuous integration and continuous deployments (CI/CD) were delivered as well.
To summarize, we delivered a data management system to enable consistent and reproducible data processing and extraction of knowledge graph; audio file processing to extract data into text transcript; transcript processing with medical NLP approaches to extract knowledge graph; and component-based architecture design using data processing pipelines.