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Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates.
Miglietta, Luca; Moniri, Ahmad; Pennisi, Ivana; Malpartida-Cardenas, Kenny; Abbas, Hala; Hill-Cawthorne, Kerri; Bolt, Frances; Jauneikaite, Elita; Davies, Frances; Holmes, Alison; Georgiou, Pantelis; Rodriguez-Manzano, Jesus.
Affiliation
  • Miglietta L; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Moniri A; Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
  • Pennisi I; Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
  • Malpartida-Cardenas K; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Abbas H; Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
  • Hill-Cawthorne K; Imperial College Healthcare NHS Trust, London, United Kingdom.
  • Bolt F; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Jauneikaite E; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Davies F; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Holmes A; Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
  • Georgiou P; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
  • Rodriguez-Manzano J; Imperial College Healthcare NHS Trust, London, United Kingdom.
Front Mol Biosci ; 8: 775299, 2021.
Article in En | MEDLINE | ID: mdl-34888355
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Front Mol Biosci Year: 2021 Document type: Article Affiliation country:
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Front Mol Biosci Year: 2021 Document type: Article Affiliation country: