Machine learning to support visual auditing of home-based lateral flow immunoassay self-test results for SARS-CoV-2 antibodies
oleh: Nathan C. K. Wong, Sepehr Meshkinfamfard, Valérian Turbé, Matthew Whitaker, Maya Moshe, Alessia Bardanzellu, Tianhong Dai, Eduardo Pignatelli, Wendy Barclay, Ara Darzi, Paul Elliott, Helen Ward, Reiko J. Tanaka, Graham S. Cooke, Rachel A. McKendry, Christina J. Atchison, Anil A. Bharath
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2022-07-01 |
Deskripsi
Wong et al. describe a machine learning approach for visual auditing of lateral flow tests for SARS-CoV-2 antibodies. Their automated analysis shows strong agreement with experts and consistently better performance than non-expert study participants at classifying positive results.