An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening von Hu, Liming, Bell, David, Antani, Sameer, Xue, Zhiyun, Yu, Kai, Horning, Matthew P, Gachuhi, Noni, Wilson, Benjamin, Jaiswal, Mayoore S, Befano, Brian, Long, L Rodney, Herrero, Rolando, Einstein, Mark H, Burk, Robert D, Demarco, Maria, Gage, Julia C, Rodriguez, Ana Cecilia, Wentzensen, Nicolas, Schiffman, Mark

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Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound von Kessler, David, Zhu, Meihua, Gregory, Cynthia R, Mehanian, Courosh, Avila, Jailyn, Avitable, Nick, Coneybeare, Di, Das, Devjani, Dessie, Almaz, Kennedy, Thomas M, Rabiner, Joni, Malia, Laurie, Ng, Lorraine, Nye, Megan, Vindas, Marc, Weimersheimer, Peter, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton, Zheng, Xinliang, Horning, Matthew P, Stone, Mike, Wang, Fen, Lancioni, Christina

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Performance of a fully-automated system on a WHO malaria microscopy evaluation slide set von Horning, Matthew P, Delahunt, Charles B, Bachman, Christine M, Luchavez, Jennifer, Luna, Christian, Hu, Liming, Jaiswal, Mayoore S, Thompson, Clay M, Kulhare, Sourabh, Janko, Samantha, Wilson, Benjamin K, Ostbye, Travis, Mehanian, Martha, Gebrehiwot, Roman, Yun, Grace, Bell, David, Proux, Stephane, Carter, Jane Y, Oyibo, Wellington, Gamboa, Dionicia, Dhorda, Mehul, Vongpromek, Ranitha, Chiodini, Peter L, Ogutu, Bernhards, Long, Earl G, Tun, Kyaw, Burkot, Thomas R, Lilley, Ken, Mehanian, Courosh

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Internal validation of Automated Visual Evaluation (AVE) on smartphone images for cervical cancer screening in a prospective study in Zambia von Hu, Liming, Mwanahamuntu, Mulindi H., Sahasrabuddhe, Vikrant V., Barrett, Caroline, Horning, Matthew P., Shah, Ishan, Laverriere, Zohreh, Banik, Dipayan, Ji, Ye, Shibemba, Aaron Lunda, Chisele, Samson, Munalula, Mukatimui Kalima, Kaunga, Friday, Musonda, Francis, Malyangu, Evans, Hariharan, Karen Milch, Parham, Groesbeck P.

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Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning von Das, Debashish, Vongpromek, Ranitha, Assawariyathipat, Thanawat, Srinamon, Ketsanee, Kennon, Kalynn, Stepniewska, Kasia, Ghose, Aniruddha, Sayeed, Abdullah Abu, Faiz, M Abul, Netto, Rebeca Linhares Abreu, Siqueira, Andre, Yerbanga, Serge R, Ouédraogo, Jean Bosco, Callery, James J, Peto, Thomas J, Tripura, Rupam, Koukouikila-Koussounda, Felix, Ntoumi, Francine, Ong'echa, John Michael, Ogutu, Bernhards, Ghimire, Prakash, Marfurt, Jutta, Ley, Benedikt, Seck, Amadou, Ndiaye, Magatte, Moodley, Bhavani, Sun, Lisa Ming, Archasuksan, Laypaw, Proux, Stephane, Nsobya, Sam L, Rosenthal, Philip J, Horning, Matthew P, McGuire, Shawn K, Mehanian, Courosh, Burkot, Stephen, Delahunt, Charles B, Bachman, Christine, Price, Ric N, Dondorp, Arjen M, Chappuis, François, Guérin, Philippe J, Dhorda, Mehul

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Limitations of haemozoin-based diagnosis of Plasmodium falciparum using dark-field microscopy von Delahunt, Charles, Horning, Matthew P, Wilson, Benjamin K, Proctor, Joshua L, Hegg, Michael C

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Detection of malarial byproduct hemozoin utilizing its unique scattering properties von Wilson, Benjamin K, Behrend, Matthew R, Horning, Matthew P, Hegg, Michael C

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A paper microfluidic cartridge for automated staining of malaria parasites with an optically transparent microscopy window von Horning, Matthew P, Delahunt, Charles B, Singh, S Ryan, Garing, Spencer H, Nichols, Kevin P

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How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound von Yu, Menghan, Kulhare, Sourabh, Mehanian, Courosh, Delahunt, Charles B., Shea, Daniel E., Laverriere, Zohreh, Shah, Ishan, Horning, Matthew P.

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Metrics to guide development of machine learning algorithms for malaria diagnosis von Delahunt, Charles B., Gachuhi, Noni, Horning, Matthew P.

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Nanogap quantum dot photodetectors with high sensitivity and bandwidth von Hegg, Michael C., Horning, Matthew P., Baehr-Jones, Tom, Hochberg, Michael, Lin, Lih Y.

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Evaluation of an automated microscope using machine learning for the detection of malaria in travelers returned to the UK von Rees-Channer, Roxanne R., Bachman, Christine M., Grignard, Lynn, Gatton, Michelle L., Burkot, Stephen, Horning, Matthew P., Delahunt, Charles B., Hu, Liming, Mehanian, Courosh, Thompson, Clay M., Woods, Katherine, Lansdell, Paul, Shah, Sonal, Chiodini, Peter L.

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A paper microfluidic cartridge for automated staining of malaria parasites with an optically transparent microscopy windowElectronic supplementary information (ESI) available. See... von Horning, Matthew P, Delahunt, Charles B, Singh, S. Ryan, Garing, Spencer H, Nichols, Kevin P

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Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound von David Kessler, Meihua Zhu, Cynthia R Gregory, Courosh Mehanian, Jailyn Avila, Nick Avitable, Di Coneybeare, Devjani Das, Almaz Dessie, Thomas M Kennedy, Joni Rabiner, Laurie Malia, Lorraine Ng, Megan Nye, Marc Vindas, Peter Weimersheimer, Sourabh Kulhare, Rachel Millin, Kenton Gregory, Xinliang Zheng, Matthew P Horning, Mike Stone, Fen Wang, Christina Lancioni

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Driving down Poisson error can offset classification error in clinical tasks von Delahunt, Charles B, Mehanian, Courosh, Horning, Matthew P

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Metrics to guide development of machine learning algorithms for malaria diagnosis von Delahunt, Charles B, Gachuhi, Noni, Horning, Matthew P

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How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound von Yu, Menghan, Kulhare, Sourabh, Mehanian, Courosh, Delahunt, Charles B, Shea, Daniel E, Laverriere, Zohreh, Shah, Ishan, Horning, Matthew P

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Driving down Poisson error can offset classification error in clinical tasks von Delahunt, Charles B, Mehanian, Courosh, Horning, Matthew P

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Metrics to guide development of machine learning algorithms for malaria diagnosis von Delahunt, Charles B, Gachuhi, Noni, Horning, Matthew P

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AUTOMATED MICROSCOPY SCANNING SYSTEMS AND METHODS von HU, Liming, HORNING, Matthew P, MEHANIAN, Courosh, MCGUIRE, Shawn

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