Melissa, a provider of global contact data quality and identity verification solutions, is releasing a suite of advanced artificial intelligence (AI) solutions that combine machine reasoning, natural language processing, and machine learning.
Melissa Informatics’ Sentient (MIS) solution is a new and unique set of clinical data quality and integration tools that turn diverse, dirty, and disconnected data into a clean, research-ready data resource.
“Too often, clinical data is expensively gathered and under-valued,” said Bob Stanley, senior director, customer projects, Melissa Informatics. “When you apply machine learning and machine reasoning to access, curate, and integrate this data, it becomes ready for rewarding new uses in patient care, precision medicine research, intellectual property, and unexpected new revenue.”
Melissa Informatics further demonstrates the value of AI-enabled data quality by providing real-world use cases from clinics including Parkinson’s Institute and Clinical Center (PICC) and PROOF Centre.
By using Melissa Informatics MIS technology, PICC transformed data such as unstructured text, XML, tables, tsv, image content and other data formats into a research quality, well-managed data resource. This helped the organization meet its technical goals including creating a new, unified “Parkinson’s Insight” data resource – as well as its business goals, including researching and publishing discoveries from that data, and engaging in revenue-generating partnerships based on the new data resource. Access the full case study here.
For more information about this news, visit www.melissa.com.