Author

Sheila B. Ogoma

Clinton Health Access InitiativeORCID 0000-0002-4063-6762Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1

Frequent Co-Authors

Floyd E. DowelliD· 1 shared Fredros O. OkumuiD· 1 shared George F. CorlissiD· 1 shared J. D. CharlwoodiD· 1 shared Maggy T. Sikulu-LordiD· 1 shared Marta F. MaiaiD· 1 shared Masabho P. MilaliiD· 1 shared Naveen K. BansaliD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Floyd E. DowellORCID

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1 paper

Recent·Most cited

An Autoencoder and Artificial Neural Network-based Method to Estimate Parity Status of Wild Mosquitoes from Near-infrared Spectra

Masabho P. Milali, Samson S. Kiware, Nicodem James Govella, Fredros O. Okumu, Naveen K. Bansal, Serdar Bozdag, J. D. Charlwood, Marta F. Maia, Sheila B. Ogoma, Floyd E. Dowell, George F. Corliss, Maggy T. Sikulu-Lord, Richard J. Povinelli

This paper develops an autoencoder and ANN model to estimate parity status of wild mosquitoes using NIR spectra, achieving high accuracy across multiple datasets.

PLoS ONE · Jun 18, 2020Peer-reviewedBioinformatics