Unlock Discovery, Collaboration, Revenue & Personalized Care
Real-world clinical and healthcare research data is unusually valuable, but it is also unusually complex and diverse. Life science research data deals with diverse terminologies and ever-evolving patient data that even the most disciplined clinical practices will generate dirty data. Solve those complex data quality problems with the best AI-enabled products. Melissa combines over 35 years of deep domain knowledge with the latest in machine learning and reasoning to provide tools that work for you.
6-Step Guide to Turn Clinical Data into Gold For Better Patient Care & New Revenue
Read our 6-Step Guide to turn your disconnected and dirty laboratory and clinical study data into a clean, unified data resource, and learn how Melissa Informatics can help you tap your under-used data goldmine.Download Brochure
Utilize semantic technology to integrate data and solve common knowledge and project management problems.
Validate, correct and standardize an individual’s address, name, phone, and email, and merge duplicate records for a 360-degree view of patient information.
Verify an individual’s identity including SSN/National ID check, age verification and date of birth/date of death.
Add latitude/longitude coordinates to postal addresses, demographics and property data for enhanced insight and analysis.
Autocomplete drug names during data entry to save time, mitigate data entry errors and avoid confusion.
Enhance your data repository regularly with new drug information, issued warnings, recent discoveries, DDI (Drug-Drug Interaction), and ADE (Adverse Drug Effects).
Access the most useful, comprehensive, integrated data (“content”), terminology standards (“lexicons”) and semantic data models (“ontologies”) for drugs, genes, proteins and diseases.
Utilize patented machine reasoning and reference ontologies to identify and establish common terms, units and formats.