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Development of machine learning models for the surveillance of colon surgical site infections.
Cho, S Y; Kim, Z; Chung, D R; Cho, B H; Chung, M J; Kim, J H; Jeong, J.
Afiliação
  • Cho SY; Center for Infection Prevention and Control, Samsung Medical Center, Seoul, Republic of Korea; Division of Infectious Diseases, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Kim Z; Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea; Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Chung DR; Center for Infection Prevention and Control, Samsung Medical Center, Seoul, Republic of Korea; Division of Infectious Diseases, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. Electronic address: iddrchung@gmail.com.
  • Cho BH; Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, Republic of Korea; Institute of Biomedical Informatics, School of Medicine, CHA University, Seongnam, Republic of Korea.
  • Chung MJ; Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea; Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Kim JH; Department of Biomedical Science, Korea University College of Medicine, Seoul, Republic of Korea.
  • Jeong J; Center for Infection Prevention and Control, Samsung Medical Center, Seoul, Republic of Korea.
J Hosp Infect ; 146: 224-231, 2024 Apr.
Article em En | MEDLINE | ID: mdl-37094715
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Screening_studies Idioma: En Revista: J Hosp Infect Ano de publicação: 2024 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Screening_studies Idioma: En Revista: J Hosp Infect Ano de publicação: 2024 Tipo de documento: Article