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Shot in the arm: AI's healthcare journey
March 2021
|Gulf Business
Hospitals generate massive amounts of data from the hospital information system (HIS), picture archiving and communication system (PACS) and laboratory information system (LIS). Analysing this data can have a major impact on health outcomes. The technology to securely and efficiently analyse this massive trove of data to gain any meaningful insights has been wanting, until now. AI, which by nature requires the ingestion of enormous amounts of data, was built for these types of environments.

Aster DM Healthcare is a medical group with a presence spread across nine countries with 12 hospitals, 107 clinics and 231 pharmacies with heavy patient footfall. Using artificial intelligence, Aster is now leveraging its massive pool of data through the recently-launched Centre of Digital Health Excellence (Aster CDHE).
Aster CDHE has four platforms. Aster Databank is a platform to leverage health data to build AI algorithms. It is currently working with a leading digital data transformation partner towards collecting, synthesising, annotating and storing data from various streams such as HIS, PACS, LIS and Citizen.
The second platform is Asterstine, an inhouse AI and big data research centre which seeks to partner with tech firms to codevelop and conduct interdisciplinary research in Aster’s medical facilities. The third platform is Aster Clinical Simulation Lab, a pre-clinical productdevelopment approach for faster, and compliant evidence generation for digital health solutions. Aster’s approach helps in evidence-generation, iterative agile development, clinical data modelling and conducting early validation experiments inside the group’s infrastructure.
Aster has also launched the Digital Centralised Clinical Trial Centre, a facility that is using digital technologies to shift conventional clinical trial processes. The centre also offers a platform to SMEs and startups with limited resources to undertake clinical studies in digital technologies while enabling larger corporates to avoid operational inefficiencies.
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