Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra.

Mwanga, Emmanuel P; Siria, Doreen J; Mitton, Joshua; Mshani, Issa H; González-Jiménez, Mario; Selvaraj, Prashanth; Wynne, Klaas; Baldini, Francesco; Okumu, Fredros O; Babayan, Simon A

Mwanga, Emmanuel P; Siria, Doreen J; Mitton, Joshua; Mshani, Issa H; González-Jiménez, Mario; Selvaraj, Prashanth; Wynne, Klaas; Baldini, Francesco; Okumu, Fredros O; Babayan, Simon A.

Afiliación

Mwanga EP; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania. emwanga@ihi.or.tz.
Siria DJ; School of Biodiversity, One Health, and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK. emwanga@ihi.or.tz.
Mitton J; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania.
Mshani IH; School of Biodiversity, One Health, and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK.
González-Jiménez M; School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK.
Selvaraj P; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania.
Wynne K; School of Biodiversity, One Health, and Veterinary Medicine, University of Glasgow, Glasgow, G12 8QQ, UK.
Baldini F; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK.
Okumu FO; Institute for Disease Modelling, Bellevue, WA, 98005, USA.
Babayan SA; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK.

BMC Bioinformatics ; 24(1): 11, 2023 Jan 09.

Article en En | MEDLINE | ID: mdl-36624386

Asunto(s)

Anopheles; Malaria; Animales; Adulto; Femenino; Humanos; Mosquitos Vectores; Aprendizaje Automático

Palabras clave

Anopheles arabiensis; Convolutional neural network; Dimensionality reduction; Generalisability; Standard machine learning; Transfer learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Malaria / Anopheles Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Animals / Female / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Tanzania Pais de publicación: Reino Unido

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