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An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.

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Title: An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.
Authors: Milali MP; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania., Kiware SS; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania., Govella NJ; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania., Okumu F; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania., Bansal N; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America., Bozdag S; Department of Computer Science, Marquette University, Milwaukee, WI, United States of America., Charlwood JD; Liverpool School of Tropical Medicine, Liverpool, England, United Kingdom., Maia MF; Wellcome Trust Research Programme, Kenya Medical Research Institute, Kilifi, Kenya.; Swiss Tropical and Public Health Institute, Basel, Switzerland.; University of Basel, Basel, Switzerland., Ogoma SB; Clinton Health Access Initiative, Nairobi, Kenya., Dowell FE; Center for Grain and Animal Health Research, USDA, Agricultural Research Service, Manhattan, KS, United States of America., Corliss GF; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI, United States of America., Sikulu-Lord MT; The School of Public Health, University of Queensland, Brisbane, Queensland, Australia., Povinelli RJ; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI, United States of America.
Source: PloS one [PLoS One] 2020 Jun 18; Vol. 15 (6), pp. e0234557. Date of Electronic Publication: 2020 Jun 18 (Print Publication: 2020).
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.
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  Data: <searchLink fieldCode="AU" term="%22Milali+MP%22">Milali MP</searchLink>; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania.<br /><searchLink fieldCode="AU" term="%22Kiware+SS%22">Kiware SS</searchLink>; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania.<br /><searchLink fieldCode="AU" term="%22Govella+NJ%22">Govella NJ</searchLink>; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania.<br /><searchLink fieldCode="AU" term="%22Okumu+F%22">Okumu F</searchLink>; Environmental Health and Ecological Sciences Thematic Group, Ifakara Health Institute, Ifakara, Tanzania.<br /><searchLink fieldCode="AU" term="%22Bansal+N%22">Bansal N</searchLink>; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.<br /><searchLink fieldCode="AU" term="%22Bozdag+S%22">Bozdag S</searchLink>; Department of Computer Science, Marquette University, Milwaukee, WI, United States of America.<br /><searchLink fieldCode="AU" term="%22Charlwood+JD%22">Charlwood JD</searchLink>; Liverpool School of Tropical Medicine, Liverpool, England, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Maia+MF%22">Maia MF</searchLink>; Wellcome Trust Research Programme, Kenya Medical Research Institute, Kilifi, Kenya.; Swiss Tropical and Public Health Institute, Basel, Switzerland.; University of Basel, Basel, Switzerland.<br /><searchLink fieldCode="AU" term="%22Ogoma+SB%22">Ogoma SB</searchLink>; Clinton Health Access Initiative, Nairobi, Kenya.<br /><searchLink fieldCode="AU" term="%22Dowell+FE%22">Dowell FE</searchLink>; Center for Grain and Animal Health Research, USDA, Agricultural Research Service, Manhattan, KS, United States of America.<br /><searchLink fieldCode="AU" term="%22Corliss+GF%22">Corliss GF</searchLink>; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI, United States of America.<br /><searchLink fieldCode="AU" term="%22Sikulu-Lord+MT%22">Sikulu-Lord MT</searchLink>; The School of Public Health, University of Queensland, Brisbane, Queensland, Australia.<br /><searchLink fieldCode="AU" term="%22Povinelli+RJ%22">Povinelli RJ</searchLink>; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI, United States of America.; Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI, United States of America.
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