Your browser doesn't support javascript.
loading
Development of a Machine Learning Model to Estimate US Firearm Homicides in Near Real Time.
Swedo, Elizabeth A; Alic, Alen; Law, Royal K; Sumner, Steven A; Chen, May S; Zwald, Marissa L; Van Dyke, Miriam E; Bowen, Daniel A; Mercy, James A.
Afiliación
  • Swedo EA; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Alic A; Division of Injury Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Law RK; Division of Injury Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Sumner SA; Office of Strategy and Innovation, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Chen MS; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Zwald ML; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Van Dyke ME; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Bowen DA; Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia.
  • Mercy JA; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.
JAMA Netw Open ; 6(3): e233413, 2023 03 01.
Article en En | MEDLINE | ID: mdl-36930150
Asunto(s)
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Heridas por Arma de Fuego / Modelos Estadísticos / Homicidio Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2023 Tipo del documento: Article País de afiliación: Georgia
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Heridas por Arma de Fuego / Modelos Estadísticos / Homicidio Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2023 Tipo del documento: Article País de afiliación: Georgia