Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Arunachalam Narayanaswamy"'
Autor:
Lauren Schiff, Bianca Migliori, Ye Chen, Deidre Carter, Caitlyn Bonilla, Jenna Hall, Minjie Fan, Edmund Tam, Sara Ahadi, Brodie Fischbacher, Anton Geraschenko, Christopher J. Hunter, Subhashini Venugopalan, Sean DesMarteau, Arunachalam Narayanaswamy, Selwyn Jacob, Zan Armstrong, Peter Ferrarotto, Brian Williams, Geoff Buckley-Herd, Jon Hazard, Jordan Goldberg, Marc Coram, Reid Otto, Edward A. Baltz, Laura Andres-Martin, Orion Pritchard, Alyssa Duren-Lubanski, Ameya Daigavane, Kathryn Reggio, NYSCF Global Stem Cell Array® Team, Phillip C. Nelson, Michael Frumkin, Susan L. Solomon, Lauren Bauer, Raeka S. Aiyar, Elizabeth Schwarzbach, Scott A. Noggle, Frederick J. Monsma, Daniel Paull, Marc Berndl, Samuel J. Yang, Bjarki Johannesson
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
By coupling robotic cell culture systems with artificial intelligence–powered image analysis, Schiff et al. identify previously unseen characteristics of Parkinson’s disease in patient skin cells that distinguish them from healthy controls.
Externí odkaz:
https://doaj.org/article/9d8265097577462f83aa83bf77ad2240
Autor:
Avinash V. Varadarajan, Pinal Bavishi, Paisan Ruamviboonsuk, Peranut Chotcomwongse, Subhashini Venugopalan, Arunachalam Narayanaswamy, Jorge Cuadros, Kuniyoshi Kanai, George Bresnick, Mongkol Tadarati, Sukhum Silpa-archa, Jirawut Limwattanayingyong, Variya Nganthavee, Joseph R. Ledsam, Pearse A. Keane, Greg S. Corrado, Lily Peng, Dale R. Webster
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020)
Diabetic eye disease is a cause of preventable blindness and accurate and timely referral of patients with diabetic macular edema is important to start treatment. Here the authors present a deep learning model that can predict the presence of diabeti
Externí odkaz:
https://doaj.org/article/00d3202651b84a36837950c21fab3fb0
Autor:
Samuel J. Yang, Marc Berndl, D. Michael Ando, Mariya Barch, Arunachalam Narayanaswamy, Eric Christiansen, Stephan Hoyer, Chris Roat, Jane Hung, Curtis T. Rueden, Asim Shankar, Steven Finkbeiner, Philip Nelson
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-9 (2018)
Abstract Background Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis
Externí odkaz:
https://doaj.org/article/5d2ce73d279747d2bfbef81a96bfc6be
Autor:
Jake Baum, Michelle Dimon, Wesley Wei Qian, George W. Ashdown, Jian Peng, D. Michael Ando, Subhashini Venugopalan, Arunachalam Narayanaswamy, Cassandra Xia
Publikováno v:
Bioinformatics. 36:i875-i883
Motivation Advances in automation and imaging have made it possible to capture a large image dataset that spans multiple experimental batches of data. However, accurate biological comparison across the batches is challenged by batch-to-batch variatio
Autor:
Lily Peng, Mongkol Tadarati, Subhashini Venugopalan, Pinal Bavishi, Greg S. Corrado, George H. Bresnick, Variya Nganthavee, Jirawut Limwattanayingyong, Kuniyoshi Kanai, Paisan Ruamviboonsuk, Joseph R. Ledsam, Avinash V. Varadarajan, Jorge Cuadros, Sukhum Silpa-archa, Dale R. Webster, Peranut Chotcomwongse, Pearse A. Keane, Arunachalam Narayanaswamy
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020)
Nature communications, vol 11, iss 1
Nature Communications
Nature communications, vol 11, iss 1
Nature Communications
Center-involved diabetic macular edema (ci-DME) is a major cause of vision loss. Although the gold standard for diagnosis involves 3D imaging, 2D imaging by fundus photography is usually used in screening settings, resulting in high false-positive an
Autor:
Samuel Yang, Arunachalam Narayanaswamy, Philip C. Nelson, Nina R. Makhortova, D. Michael Ando, Anton Geraschenko, Liyong Deng, Wendy K. Chung, Brian Williams, Lee L. Rubin, Zan Armstrong, Marc Berndl, Jon Hazard, Liadan O'Callaghan, Thorsten M. Schlaeger, Subhashini Venugopalan, Minjie Fan, Scott Lipnick, Dosh Whye
Publikováno v:
Slas Discovery
The etiological underpinnings of many CNS disorders are not well understood. This is likely due to the fact that individual diseases aggregate numerous pathological subtypes, each associated with a complex landscape of genetic risk factors. To overco
Autor:
Lauren, Schiff, Bianca, Migliori, Ye, Chen, Deidre, Carter, Caitlyn, Bonilla, Jenna, Hall, Minjie, Fan, Edmund, Tam, Sara, Ahadi, Brodie, Fischbacher, Anton, Geraschenko, Christopher J, Hunter, Subhashini, Venugopalan, Sean, DesMarteau, Arunachalam, Narayanaswamy, Selwyn, Jacob, Zan, Armstrong, Peter, Ferrarotto, Brian, Williams, Geoff, Buckley-Herd, Jon, Hazard, Jordan, Goldberg, Marc, Coram, Reid, Otto, Edward A, Baltz, Laura, Andres-Martin, Orion, Pritchard, Alyssa, Duren-Lubanski, Ameya, Daigavane, Kathryn, Reggio, Phillip C, Nelson, Michael, Frumkin, Susan L, Solomon, Lauren, Bauer, Raeka S, Aiyar, Elizabeth, Schwarzbach, Scott A, Noggle, Frederick J, Monsma, Daniel, Paull, Marc, Berndl, Samuel J, Yang, Bjarki, Johannesson
Publikováno v:
Nature communications. 13(1)
Drug discovery for diseases such as Parkinson’s disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and d
Autor:
Minjie Fan, Samuel Yang, Orion Pritchard, Sean DesMarteau, Zan Armstrong, Selwyn Jacob, Marc Coram, Peter Ferrarotto, Edward A. Baltz, Lauren Schiff, Edmund Tam, Alyssa Duren-Lubanski, Ameya Daigavane, Geoff Buckley-Herd, Brian Williams, Elizabeth Schwarzbach, Raeka S. Aiyar, Jordan Goldberg, Jenna Hall, Daniel Paull, Deidre Carter, Marc Berndl, Scott Noggle, Reid Otto, Jon Hazard, Frederick J. Monsma, Lauren Bauer, Caitlyn Bonilla, Brodie Fischbacher, Bianca Migliori, Ye Chen, Sara Ahadi, Bjarki Johannesson, Subhashini Venugopalan, Christopher J. Hunter, Arunachalam Narayanaswamy, Anton Geraschenko, Kathryn Reggio, Laura Andres-Martin
Drug discovery for diseases such as Parkinson’s disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0736c9ee7dda2c99486a56f923ee84dc
https://doi.org/10.1101/2020.11.13.380576
https://doi.org/10.1101/2020.11.13.380576
Autor:
D. Michael Ando, Arunachalam Narayanaswamy, Cassandra Xia, Wesley Wei Qian, Jian Peng, Subhashini Venugopalan
Advances in automation and imaging have made it possible to capture large image datasets for experiments that span multiple weeks with multiple experimental batches of data. However, accurate biological comparisons across the batches is challenged by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8e0f69aa7dd2d89504d2aafe0f4e818
https://doi.org/10.1101/2020.02.07.939215
https://doi.org/10.1101/2020.02.07.939215
Autor:
Lily Peng, Pinal Bavishi, Dale R. Webster, Arunachalam Narayanaswamy, Michael Brenner, Philip C. Nelson, Avinash V. Varadarajan, Subhashini Venugopalan, Greg S. Corrado, Paisan Ruamviboonsuk
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597092
MICCAI (1)
MICCAI (1)
Model explanation techniques play a critical role in understanding the source of a model’s performance and making its decisions transparent. Here we investigate if explanation techniques can also be used as a mechanism for scientific discovery. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acf1ab392f22e6f90dd12f933ffcbeba
https://doi.org/10.1007/978-3-030-59710-8_27
https://doi.org/10.1007/978-3-030-59710-8_27