DOC Search is an industry-leading search engine for medical literature, powered by natural language processing (NLP) and artificial intelligence (AI) technology. Users can run concept-based searches across a broad variety of medical data sources to identify, analyze, and monitor available evidence for any topic area. Applying deep learning AI technology to DRE’s decade of ontology management experience harmonizes search terms across domains, resulting in accurate and comprehensive search queries.
DRE software engineers, researchers, and ontology specialists have refined the ontology mapping algorithm to include all synonyms of a concept, drawing upon a vast array of medical dictionaries. Concepts and additional search features are applied to a constantly updated resource based on PubMed, ClinicalTrials.gov, EPAR, and public RSS feeds such as news outlets (see also: ASCO DOC Search).
Searches conducted in this expansive dataset allow researchers, business leaders, and other healthcare stakeholders to quickly:
- Understand the quantity and nature of medical evidence for any given topic.
- Refine the available evidence into important categories such as study type and geographic location.
- Identify thought leaders and their collaboration networks.
- Evaluate the likelihood that new evidence represents a safety signal.
- Partner with DRE to integrate this technology into existing data streams and to enhance internal data repositories.
Search across clinical databases for customized tasks:
- Filter by safety, efficacy, prevention, diagnosis, screening, therapy, prognosis, care management, and more.
- Review a summary table of the most commonly reported characteristics, interventions, and outcomes in an area of interest, to understand the patient population, therapeutic landscape, and available study endpoints.
- Conduct rapid feasibility assessments of the evidence landscape to determine if there is sufficient data available to support a given research question.
- Determine distribution of interventions across disease states and adverse events.
- Identify post hoc analyses or associated publications based on the same clinical trial.
- Set signals for surveillance and updating.
- Use international ontology & taxonomy mappings from natural language search terms to develop comprehensive search strings.
- Rapid Assessment
- Systematic Literature
- Competitor Label
- Focused Literature
- Payer Dossier
Current DOC Search database statistics: