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. |
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| 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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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0234557 |
