Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sonia Phene"'
Autor:
Beverly Freeman, Naama Hammel, Sonia Phene, Abigail Huang, Rebecca Ackermann, Olga Kanzheleva, Miles Hutson, Caitlin Taggart, Quang Duong, Rory Sayres
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 9:60-71
Data quality is a key concern for artificial intelligence (AI) efforts that rely on crowdsourced data collection. In the domain of medicine in particular, labeled data must meet high quality standards, or the resulting AI may perpetuate biases or lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f024cd9ae3b947d074716c3dc73818dc
https://doi.org/10.1609/hcomp.v9i1.18940
https://doi.org/10.1609/hcomp.v9i1.18940
Autor:
Jeffery B. Alvarez, Jean-Emmanuel Bibault, Anita Burgun, Jinzheng Cai, Zhidong Cao, Ken Chang, Jonathan H. Chen, William C. Chen, Mildred Cho, Peter Jaeho Cho, Toby C. Cornish, Anthony Costa, Andre Dekker, Karen Drukker, Jessilyn Dunn, Okyaz Eminaga, Bradley J. Erickson, Laure Fournier, Sanjiv Sam Gambhir, Efstathios D. Gennatas, Maryellen L. Giger, Iva Halilaj, Adam P. Harrison, Bryan He, Julian C. Hong, Dakai Jin, Michael C. Jin, Arthur Jochems, Jayashree Kalpathy-Cramer, Daniel S. Kapp, Mehran Karimzadeh, William Karnes, Philippe Lambin, Curtis P. Langlotz, Joonsang Lee, Hui Li, Joseph C. Liao, Anthony L. Lin, Rebecca Y. Lin, Yun Liu, Le Lu, David Magnus, Chris McIntosh, Shun Miao, James K. Min, Daniel B. Neill, Eric Karl Oermann, David Ouyang, Lily Peng, Sonia Phene, Maarten G. Poirot, Jennifer L. Quon, Daniel Ranti, Arvind Rao, Ramesh Raskar, Christopher Rombaoa, Daniel L. Rubin, Jason Samarasena, Jayne Seekins, Karthik Seetharam, Emily Shearer, Adam Sibley, Karnika Singh, Praveer Singh, Margarita Sordo, Duminda Suraweera, Aly Al-Amyn Valliani, Yvonka van Wijk, Praneeth Vepakomma, Bo Wang, Ge Wang, Nicholas Wang, Yirui Wang, Elisa Warner, Mattea Welch, Kimberly Wong, Zhenqin Wu, Fuyong Xing, Lei Xing, Ke Yan, Pingkun Yan, Lu Yang, Kristen W. Yeom, Robin Zachariah, Daniel Zeng, Lin Zhang, Ling Zhang, Xuhong Zhang, Li Zhou, James Zou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa320ae1c368b21aa83be70ba954784f
https://doi.org/10.1016/b978-0-12-821259-2.00035-1
https://doi.org/10.1016/b978-0-12-821259-2.00035-1
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9780128212592
Diabetic retinopathy (DR) is one of the fastest growing causes of blindness and has prompted the implementation of national screening programs. To help address the shortage of experts to grade images for signs of DR, there has been a surge of interes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d2074fa729d26a38f269211283bb801
https://doi.org/10.1016/b978-0-12-821259-2.00013-2
https://doi.org/10.1016/b978-0-12-821259-2.00013-2
Autor:
Paul J. Foster, D. Sculley, Elizabeth H. Dorfman, Farhad Hormozdiari, Cory Y. McLean, Anthony P Khawaja, Justin Cosentino, Babak Alipanahi, Sonia Phene, Emanuel Schorsch, Babak Behsaz, Zachary R. McCaw, Naama Hammel, Lily Peng, Andrew Carroll
Publikováno v:
American Journal of Human Genetics
Summary Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we develop a machine learning (ML) model to predict glaucomatous optic nerve head features fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e863106ce6486c66c3addd4df46623ea
https://pubmed.ncbi.nlm.nih.gov/34077760
https://pubmed.ncbi.nlm.nih.gov/34077760
Publikováno v:
Ophthalmology. 127(8)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1fdb7170a3218d5b354cb07e48ceae4
https://pubmed.ncbi.nlm.nih.gov/32703394
https://pubmed.ncbi.nlm.nih.gov/32703394
Autor:
Jonathan Krause, Jirawut Limwattanayingyong, Jeffrey Tan, Dale R. Webster, Paisan Ruamviboonsuk, Chetan Rao, Oscar Kuruvilla, Chawawat Kangwanwongpaisan, Sonia Phene, Mongkol Tadarati, Chainarong Luengchaichawang, Kornwipa Hemarat, Sukhum Silpa-archa, Chaiyasit Thepchatri, Surapong Orprayoon, Srirut Kawinpanitan, Peranut Chotcomwongse, Korntip Mitvongsa, Kasumi Widner, Jitumporn Fuangkaew, Rory Sayres, Ramase Sukumalpaiboon, Rajiv Raman, Sarawuth Saree, Bilson J. L. Campana, Lamyong Chualinpha, Siriporn Lawanasakol, Lalita Wongpichedchai, Jesse J. Jung, Greg S. Corrado, Pipat Kongsap, Lily Peng
Publikováno v:
NPJ Digital Medicine
npj Digital Medicine, Vol 2, Iss 1, Pp 1-1 (2019)
npj Digital Medicine, Vol 2, Iss 1, Pp 1-1 (2019)
Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::959488a8e9b9235bbbbc81d2bc5c2171
http://europepmc.org/articles/PMC6650411
http://europepmc.org/articles/PMC6650411
Autor:
Bilson J. L. Campana, Pipat Kongsap, Rajiv Raman, Peranut Chotcomwongse, Chaiyasit Thepchatri, Korntip Mitvongsa, Greg S. Corrado, Surapong Orprayoon, Srirut Kawinpanitan, Sukhum Silpa-archa, Jitumporn Fuangkaew, Kasumi Widner, Chetan Rao, Jirawut Limwattanayingyong, Jeffrey Tan, Siriporn Lawanasakol, Lalita Wongpichedchai, Oscar Kuruvilla, Ramase Sukumalpaiboon, Jesse J. Jung, Chawawat Kangwanwongpaisan, Sonia Phene, Kornwipa Hemarat, Jonathan Krause, Lily Peng, Mongkol Tadarati, Paisan Ruamviboonsuk, Lamyong Chualinpha, Chainarong Luengchaichawang, Sarawuth Saree, Rory Sayres, Dale R. Webster
Publikováno v:
NPJ Digital Medicine
npj Digital Medicine, Vol 2, Iss 1, Pp 1-9 (2019)
npj Digital Medicine, Vol 2, Iss 1, Pp 1-9 (2019)
Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00db6f5027b2d043064940f5e52b6e6b
http://europepmc.org/articles/PMC6550283
http://europepmc.org/articles/PMC6550283