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Rapidly adaptable automated interpretation of point-of-care COVID-19 diagnostics.
Arumugam, Siddarth; Ma, Jiawei; Macar, Uzay; Han, Guangxing; McAulay, Kathrine; Ingram, Darrell; Ying, Alex; Chellani, Harshit Harpaldas; Chern, Terry; Reilly, Kenta; Colburn, David A M; Stanciu, Robert; Duffy, Craig; Williams, Ashley; Grys, Thomas; Chang, Shih-Fu; Sia, Samuel K.
Afiliação
  • Arumugam S; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Ma J; Department of Computer Science, Columbia University, New York, NY, 10027, USA.
  • Macar U; Department of Computer Science, Columbia University, New York, NY, 10027, USA.
  • Han G; Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA.
  • McAulay K; Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, AZ, 85054, USA.
  • Ingram D; Safe Health Systems, Inc., Los Angeles, CA, 90036, USA.
  • Ying A; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Chellani HH; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Chern T; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Reilly K; Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, AZ, 85054, USA.
  • Colburn DAM; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Stanciu R; Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
  • Duffy C; Safe Health Systems, Inc., Los Angeles, CA, 90036, USA.
  • Williams A; Safe Health Systems, Inc., Los Angeles, CA, 90036, USA.
  • Grys T; Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, AZ, 85054, USA.
  • Chang SF; Department of Computer Science, Columbia University, New York, NY, 10027, USA. sc250@columbia.edu.
  • Sia SK; Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA. sc250@columbia.edu.
Commun Med (Lond) ; 3(1): 91, 2023 Jun 23.
Article em En | MEDLINE | ID: mdl-37353603
It can be difficult to correctly interpret the results of rapid diagnostic tests that give a visual readout, such as COVID rapid tests. We developed a computational algorithm to interpret rapid test results using an image taken by a smartphone camera. This algorithm can easily be adapted for use on results from different test kits. The algorithm was accurate at interpreting results obtained by members of the public using various COVID rapid tests and diagnostic tests with similar outputs used for other infections. The use of this algorithm should enable accurate interpretation of rapid diagnostic tests by members of the public and hence enable improved medical care.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Commun Med (Lond) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Commun Med (Lond) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos