Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.

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Title: Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.
Authors: Ho C; Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; School of Public Health, Imperial College London, London, UK., Puthur C; Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK., Nabatte B; Division of Vector Borne Diseases and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda., Moore CP; Department of Chemistry, Vanderbilt University, Nashville, TN, USA.; Task Force for Global Health, Atlanta, GA, USA., Abdoel T; Mondial Diagnostics, Amsterdam, The Netherlands., Paulussen R; Mondial Diagnostics, Amsterdam, The Netherlands., Nganjimi P; Department of Engineering Science, University of Oxford, Oxford, UK., Hoekstra PT; Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands., Kabatereine NB; Division of Vector Borne Diseases and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda., Kawesa B; Mayuge District Local Government, Uganda Ministry of Health, Mayuge, Uganda., Odea J; Division of Vector Borne Diseases and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda., Bogere R; Division of Vector Borne Diseases and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda., Katushabe R; Division of Vector Borne Diseases and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda., van Dam GJ; Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands., Scherr TF; Department of Chemistry, Vanderbilt University, Nashville, TN, USA., Chami GF; Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK. goylette.chami@ndph.ox.ac.uk.
Source: Nature communications [Nat Commun] 2026 May 18. Date of Electronic Publication: 2026 May 18.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2041-1723
DOI:10.1038/s41467-026-73094-0