Search Results - "Kulhare, Sourabh"

Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound by 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

“…Severe pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who lack access to advanced diagnostic…”
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Performance of a fully-automated system on a WHO malaria microscopy evaluation slide set by 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

“…Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in…”
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A dataset of Solicited Cough Sound for Tuberculosis Triage Testing by Huddart, Sophie, Yadav, Vijay, Sieberts, Solveig K., Omberg, Larson, Raberahona, Mihaja, Rakotoarivelo, Rivo, Lyimo, Issa N., Lweno, Omar, Christopher, Devasahayam J., Nhung, Nguyen Viet, Theron, Grant, Worodria, William, Yu, Charles Y., Bachman, Christine M., Burkot, Stephen, Dewan, Puneet, Kulhare, Sourabh, Small, Peter M., Cattamanchi, Adithya, Jaganath, Devan, Grandjean Lapierre, Simon

“…Cough is a common and commonly ignored symptom of lung disease. Cough is often perceived as difficult to quantify, frequently self-limiting, and non-specific…”
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Feature detection and pneumonia diagnosis based on clinical lung ultrasound imagery using deep learning by Zheng, Xinliang, Kulhare, Sourabh, Mehanian, Courosh, Chen, Zhijie, Wilson, Ben

“…Pneumonia is a common disease with both high morbidity and mortality. The diagnosis of pneumonia remains a clinical challenge, especially in low resource…”
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Key frame extraction for salient activity recognition by Kulhare, Sourabh, Sah, Shagan, Pillai, Suhas, Ptucha, Raymond

“…Surveillance cameras have become big business, with most metropolitan cities spending millions of dollars to watch residents, both from street corners, public…”
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Deep Learning for Semantic Video Understanding by Kulhare, Sourabh

“…The field of computer vision has long strived to extract understanding from images and videos sequences. The recent flood of video data along with massive…”
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Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound by 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

“…Background and objectivesSevere pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who lack access…”
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Contrastive Self-Supervised Learning for Spatio-Temporal Analysis of Lung Ultrasound Videos by Chen, Li, Rubin, Jonathan, Ouyang, Jiahong, Balaraju, Naveen, Patil, Shubham, Mehanian, Courosh, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton W., Gregory, Cynthia R., Zhu, Meihua, Kessler, David O., Malia, Laurie, Dessie, Almaz, Rabiner, Joni, Coneybeare, Di, Shopsin, Bo, Hersh, Andrew, Madar, Cristian, Shupp, Jeffrey, Johnson, Laura S., Avila, Jacob, Dwyer, Kristin, Weimersheimer, Peter, Raju, Balasundar, Kruecker, Jochen, Chen, Alvin

“…Self-supervised learning (SSL) methods have shown promise for medical imaging applications by learning meaningful visual representations, even when the amount…”
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How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound by Yu, Menghan, Kulhare, Sourabh, Mehanian, Courosh, Delahunt, Charles B, Shea, Daniel E, Laverriere, Zohreh, Shah, Ishan, Horning, Matthew P

“…Acquiring large quantities of data and annotations is known to be effective for developing high-performing deep learning models, but is difficult and expensive…”
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Semantic Text Summarization of Long Videos by Shagan Sah, Kulhare, Sourabh, Gray, Allison, Venugopalan, Subhashini, Prud'Hommeaux, Emily, Ptucha, Raymond

“…Long videos captured by consumers are typically tied to some of the most important moments of their lives, yet ironically are often the least frequently…”
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Deep Learning Video Classification of Lung Ultrasound Features Associated with Pneumonia by Shea, Daniel E, Kulhare, Sourabh, Millin, Rachel, Laverriere, Zohreh, Mehanian, Courosh, Delahunt, Charles B, Banik, Dipayan, Zheng, Xinliang, Zhu, Meihua, Ji, Ye, Ostbye, Travis, Mehanian, Martha-Marie S, Uwajeh, Atinuke, Akinsete, Adeseye M, Wang, Fen, Horning, Matthew P

“…Ultrasound (US) imaging holds promise as a low-cost versatile, non-invasive point-of-care diagnostic modality in low-and middle-income countries (LMICs)…”
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Contrastive Self-Supervised Learning for Spatio-Temporal Analysis of Lung Ultrasound Videos by Chen, Li, Rubin, Jonathan, Ouyang, Jiahong, Balaraju, Naveen, Patil, Shubham, Mehanian, Courosh, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton W, Gregory, Cynthia R, Zhu, Meihua, Kessler, David O, Malia, Laurie, Dessie, Almaz, Rabiner, Joni, Coneybeare, Di, Shopsin, Bo, Hersh, Andrew, Madar, Cristian, Shupp, Jeffrey, Johnson, Laura S, Avila, Jacob, Dwyer, Kristin, Weimersheimer, Peter, Raju, Balasundar, Kruecker, Jochen, Chen, Alvin

“…Self-supervised learning (SSL) methods have shown promise for medical imaging applications by learning meaningful visual representations, even when the amount…”
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Weakly Semi-Supervised Detection in Lung Ultrasound Videos by Ouyang, Jiahong, Chen, Li, Li, Gary Y, Balaraju, Naveen, Patil, Shubham, Mehanian, Courosh, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton W, Gregory, Cynthia R, Zhu, Meihua, Kessler, David O, Malia, Laurie, Dessie, Almaz, Rabiner, Joni, Coneybeare, Di, Shopsin, Bo, Hersh, Andrew, Madar, Cristian, Shupp, Jeffrey, Johnson, Laura S, Avila, Jacob, Dwyer, Kristin, Weimersheimer, Peter, Raju, Balasundar, Kruecker, Jochen, Chen, Alvin

“…Frame-by-frame annotation of bounding boxes by clinical experts is often required to train fully supervised object detection models on medical video data. We…”
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Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images by Delahunt, Charles B., Gebrehiwot, Roman, Wilson, Benjamin K., Long, Earl, Proux, Stephane, Gamboa, Dionicia, Chiodini, Peter, Carter, Jane, Dhorda, Mehul, Isaboke, David, Ogutu, Bernhards, Jaiswal, Mayoore S., Oyibo, Wellington, Villasis, Elizabeth, Tun, Kyaw Myo, Bachman, Christine, Bell, David, Mehanian, Courosh, Horning, Matthew P., Janko, Samantha, Thompson, Clay M., Kulhare, Sourabh, Hu, Liming, Ostbye, Travis, Yun, Grace

“…Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species…”
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Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information by Delahunt, Charles B, Jaiswal, Mayoore S, Horning, Matthew P, Janko, Samantha, Thompson, Clay M, Kulhare, Sourabh, Hu, Liming, Ostbye, Travis, Yun, Grace, Gebrehiwot, Roman, Wilson, Benjamin K, Long, Earl, Proux, Stephane, Gamboa, Dionicia, Chiodini, Peter, Carter, Jane, Dhorda, Mehul, Isaboke, David, Ogutu, Bernhards, Oyibo, Wellington, Villasis, Elizabeth, Tun, Kyaw Myo, Bachman, Christine, Bell, David, Mehanian, Courosh

“…Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species…”
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