Home Platform Language Models Visual Clinical Biomedical Finance Legal Open Source Products Medical LLMGenerative AI models exceling in clinical text summarization, information extraction and question answering Healthcare NLP3000+ small language models for de-identification and data curation from clinical & biomedical text Generative AI LabImplement Human-in-the-loop workflows for regulatory-grade AI without coding Terminology ServerSemantic mapping of medical phrases to standard or custom code systems, concept maps, and value sets Solutions De-identificationAnonymize and obfuscate tabular, free text, FHIR, PDF, DICOM, and SVS files with regulatory-grade accuracy Data CurationAutomate and scale the creation of accurate patient registries, cohorts, quality measures, and analytics from clinical documents Patient Journey IntelligenceAutomatically integrate multimodal, longitudinal, and messy clinical data into a unified OMOP data model Register now free Online EventApril 14-16, 2026 Learn Resources UpcomingWebinarsYigit GulData Scientist at John Snow LabsJuly 2902:00 P.M | ETBeyond PHI Redaction: Automating Quasi-Identifier Discovery and Risk Analysis for Expert DeterminationSign Up Now Customers Trusted by innovative pharma and healthcare companiesSee All Case Studies Company AnnouncementSee all Sign In Home Platform Language Models Visual Clinical Biomedical Finance Legal Open Source Products Medical LLMGenerative AI models exceling in clinical text summarization, information extraction and question answering Healthcare NLP3000+ small language models for de-identification and data curation from clinical & biomedical text Generative AI LabImplement Human-in-the-loop workflows for regulatory-grade AI without coding Terminology ServerSemantic mapping of medical phrases to standard or custom code systems, concept maps, and value sets Solutions De-identificationAnonymize and obfuscate tabular, free text, FHIR, PDF, DICOM, and SVS files with regulatory-grade accuracy Data CurationAutomate and scale the creation of accurate patient registries, cohorts, quality measures, and analytics from clinical documents Patient Journey IntelligenceAutomatically integrate multimodal, longitudinal, and messy clinical data into a unified OMOP data model Register now free Online EventApril 14-16, 2026 Learn Resources UpcomingWebinarsYigit GulData Scientist at John Snow LabsJuly 2902:00 P.M | ETBeyond PHI Redaction: Automating Quasi-Identifier Discovery and Risk Analysis for Expert DeterminationSign Up Now Customers Trusted by innovative pharma and healthcare companiesSee All Case Studies Company AnnouncementSee all Sign In Description The Global Youth Tobacco Survey (GYTS) uses a standard methodology for constructing the sampling frame, selecting schools and classes, preparing questionnaires, following consistent field procedures, and using consistent data management procedures for data processing and analysis
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