Case Study: Healthcare
Analysis of Echocardiogram Data has never been this easy
A medical hospital wanted a solution that would allow them to retrieve and analyze ECG data, which was being stored in fragmented data storage with inadequate metadata.
- xpresso.ai has been used to migrate data (relational data for patient demographics, findings, text notes and image data in DICOM standard) to an integrated data lake based on Hadoop.
- The solution comprises of xpresso.ai Big Data components that includes Apache Solr as the federated search platform, seamlessly integrated to a data lake.
- xpresso.ai image processing components that use Machine Learning are employed to generate relevant metadata for each ECG image.
- The solution is enabling quick and informative image retrieval from the integrated Hadoop data lake.
- Efficiency of processing huge volumes of image metadata at scale has increased by almost 70% and is enabling end users to derive quicker insights of ECG images.