DRE-AI

The DRE AI machine learning architecture of the system dynamically links unstructured natural language, such as PubMed abstracts, with semi-structured information from other sources like clinical trial registrations and even news articles.

Doctor Evidence is Training AI-Based Technology to Distinguish Real-World Evidence in Literature Search and Monitoring

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SANTA MONICA, Calif.June 3, 2019 /PRNewswire/ -- Doctor Evidence (DRE), a global health technology and healthcare research consulting company, continues to breakthrough artificial intelligence (AI) hurdles with the ability to auto-identify research studies that are based on real-world evidence (RWE). Yesterday, at the AcademyHealth Annual Research Meeting in Washington DC, DRE presented a poster entitled, "Developing a Training Set to Teach AI-Based Technology to Distinguish Real-World Evidence in Literature Search and Monitoring." [https://academyhealth.confex.com/academyhealth/2019arm/meetingapp.cgi/Paper/33535]

DOC Search

Our database currently contains ~31.0 million documents and 1.3 million concepts (2.8 million terms).

We currently index PubMed (29.8 million), ClinicalTrials.gov (308,531), EPAR (1,371), ASCO (28,108), RSS feeds (453,795 from 233 feeds).
Number of items per feed category: news: 322,030, official: 102,525, social: 37,181

procraz-steps

Connect

Search across DailyMed and MHRA libraries by product, manufacturer, or within label sections using Doctor Evidence’s advanced synonym manager for key words or phrases, including variations on search terms.

Collect

Follow labels and searches to receive automated updates and comparisons of label versions for competitive intelligence and label review.

Analyze

Create and export comparison tables to multiple formats (Word, Excel or HTML).

EXPERIENCE

Doctor Evidence (DRE) is a software, data, and services company that has applied more than a decade of deep domain knowledge and the latest in applied artificial intelligence (AI) technology to offer clients the most robust and agile system to quickly find and analyze medical literature for their living evidence initiatives.