Author: Imran Chaudhri
At Progress MarkLogic, Imran focuses on enterprise quality genAI and NoSQL solutions for managing large diverse data integrations and analytics to the healthcare and life sciences enterprise. Imran co-founded Apixio with the vision of solving the clinical data overload problem and has been developing a HIPAA compliant clinical AI big data analytics platform. The AI platform used machine learning to identify what is truly wrong with the patient and whether best practices for treatment were being deployed. Apixio’s platform makes extensive use of cloud computing based NOSQL technologies such as Hadoop, Cassandra, and Solr. Previously, Imran co-founded Anka Systems and focused on the execution of EyeRoute's business development, product definition, engineering, and operations. EyeRoute was the world's first distributed big data ophthalmology image management system. Imran was also the IHE EyeCare Technical Committee Co-chair fostering interoperability standards. Before Anka Systems, Imran was a founder and CTO of FastTide, the worlds first operational performance based meta-content delivery network (CDN). Imran has an undergraduate degree in electrical engineering from McGill University, a Masters degree in the same field from Cornell University and over 30 years of experience in the industry.
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Benefits of Generative AI for Enterprises and Semantic Data Integration
Generative AI is rapidly becoming an integral part of enterprises. Learn about the benefits of generative AI for enterprises and integrating your semantic data. -
How to Leverage Your Own Data to Improve AI Trust & Confidence
Learn how to leverage your own business data to improve AI trust by creating custom ai training data sets and knowledge graphs. -
Decimating Data Silos With Multi-Model Databases
One of the world’s largest health systems were interested in aggregating their myriad silos of medical registries (healthcare data) and wanted to accomplish this integration by converting all their data into more than 100 billion semantic triples. Here is what we proposed. -
How NoSQL Can Help Analytics in Life Sciences
Adverse effects are often buried in mounds of data, requiring extensive filtering that can take hours. Here’s how to find ‘features’ of interest — in only minutes (if not seconds), speeding up the time it takes to get your data to the machine learning aspect of detecting signals.
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