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Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis.
Mshani IH, Siria DJ, Mwanga EP, Sow BB, Sanou R, Opiyo M, Sikulu-Lord MT, Ferguson HM, Diabate A, Wynne K, González-Jiménez M, Baldini F, Babayan SA, Okumu F. Mshani IH, et al. Malar J. 2023 Nov 10;22(1):346. doi: 10.1186/s12936-023-04780-3. Malar J. 2023. PMID: 37950315 Free PMC article. Review.
Rapid age-grading and species identification of natural mosquitoes for malaria surveillance.
Siria DJ, Sanou R, Mitton J, Mwanga EP, Niang A, Sare I, Johnson PCD, Foster GM, Belem AMG, Wynne K, Murray-Smith R, Ferguson HM, González-Jiménez M, Babayan SA, Diabaté A, Okumu FO, Baldini F. Siria DJ, et al. Nat Commun. 2022 Mar 21;13(1):1501. doi: 10.1038/s41467-022-28980-8. Nat Commun. 2022. PMID: 35314683 Free PMC article.
Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning.
González Jiménez M, Babayan SA, Khazaeli P, Doyle M, Walton F, Reedy E, Glew T, Viana M, Ranford-Cartwright L, Niang A, Siria DJ, Okumu FO, Diabaté A, Ferguson HM, Baldini F, Wynne K. González Jiménez M, et al. Wellcome Open Res. 2019 Sep 16;4:76. doi: 10.12688/wellcomeopenres.15201.3. eCollection 2019. Wellcome Open Res. 2019. PMID: 31544155 Free PMC article.
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