PanSurg, a collaborative group of clinicians, surgeons and academics from the Department of Surgery and Cancer and the Institute of Global Health Innovation at the Imperial College London, needed an efficient and cost-effective method to search, curate, and consume the massive amounts of medical data in peer reviewed studies and journal papers related to the COVID-19 pandemic. To address this need to ingest, search, curate, and consume volumes of data, PanSurg used a process called REaltime DAta Synthesis and Analysis (REDASA), which leverages Cloudwick's Amorphic Data Cloud for AWS (Amorphic) natively integrated with cutting-edge AWS technologies such as Amazon Kendra, Amazon SageMaker, and Amazon OpenSearch to help ingest, search, curate and consume the data.
Read the case study below to learn how the data is processed natively in Amorphic to make volumes of unstructured data searchable through keywords and extracted entities.