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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 This dataset includes information related to state legislation on smokefree indoor air in areas such as: Bars, Commercial Day Care Centers, Government Multi-Unit Housing, Government Worksites, Home-Based Day Care Centers, Hotels and Motels, Personal Vehicles, Private Multi-Unit Housing, Private Worksites, Restaurants, Bingo Halls, Casinos, Enclosed Arenas, Grocery Stores, Hospitals, Hospital Campuses, Malls, Mental Health Outpatient and Residential Facilities, Prisons, Public Transportation, Racetrack Casinos, Substance Abuse Outpatient and Residential Facilities

The biggest unknown for vapers is what to expect over the long term

Discussion Recommendations Without stricter interventions and policies, teenagers and young adult vapers will continue to be at risk of multiple health problems associated with e-cigarettes

doi: 10.1038/nn1580

In fact, after 1 year of having stopped smoking, your risk of heart attack would have halved compared with a regular smokers, and after 10 years, the risk of death from lung cancer will have halved again