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Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections.
Burton, Ross J; Albur, Mahableshwar; Eberl, Matthias; Cuff, Simone M.
Affiliation
  • Burton RJ; Department of Infection Sciences, Severn Pathology, Bristol, BS10 5NB, UK. BurtonRJ@cardiff.ac.uk.
  • Albur M; Division of Infection and Immunity, School of Medicine, Cardiff University, Henry Wellcome Building, Heath Park, Cardiff, CF14 4XN, UK. BurtonRJ@cardiff.ac.uk.
  • Eberl M; Department of Infection Sciences, Severn Pathology, Bristol, BS10 5NB, UK.
  • Cuff SM; Division of Infection and Immunity, School of Medicine, Cardiff University, Henry Wellcome Building, Heath Park, Cardiff, CF14 4XN, UK.
BMC Med Inform Decis Mak ; 19(1): 171, 2019 08 23.
Article in En | MEDLINE | ID: mdl-31443706
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Tract Infections / Artificial Intelligence / Workload / Machine Learning Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Language: En Journal: BMC Med Inform Decis Mak Journal subject: INFORMATICA MEDICA Year: 2019 Document type: Article Affiliation country: Country of publication:
Fulltext
Add to My VHL
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Tract Infections / Artificial Intelligence / Workload / Machine Learning Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Language: En Journal: BMC Med Inform Decis Mak Journal subject: INFORMATICA MEDICA Year: 2019 Document type: Article Affiliation country: Country of publication: