Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Lotter, William"'
Explainability is a longstanding challenge in deep learning, especially in high-stakes domains like healthcare. Common explainability methods highlight image regions that drive an AI model's decision. Humans, however, heavily rely on language to conv
Externí odkaz:
http://arxiv.org/abs/2311.10933
Autor:
Wan, Guihong *, Chen, Wenxin *, Khattab, Sara *, Roster, Katie, Nguyen, Nga, Yan, Boshen, Rajeh, Ahmad, Seo, Jayhyun, Rashdan, Hannah, Zubiri, Leyre, Hadfield, Matthew J, Demehri, Shadmehr, Yu, Kun-Hsing, Lotter, William, Gusev, Alexander, LeBoeuf, Nicole R, Reynolds, Kerry L, Kwatra, Shawn G, Semenov, Yevgeniy R *
Publikováno v:
In The Lancet Oncology August 2024 25(8):1053-1069
Data scarcity and class imbalance are two fundamental challenges in many machine learning applications to healthcare. Breast cancer classification in mammography exemplifies these challenges, with a malignancy rate of around 0.5% in a screening popul
Externí odkaz:
http://arxiv.org/abs/2006.00086
Autor:
Lotter, William, Diab, Abdul Rahman, Haslam, Bryan, Kim, Jiye G., Grisot, Giorgia, Wu, Eric, Wu, Kevin, Onieva, Jorge Onieva, Boxerman, Jerrold L., Wang, Meiyun, Bandler, Mack, Vijayaraghavan, Gopal, Sorensen, A. Gregory
Breast cancer remains a global challenge, causing over 1 million deaths globally in 2018. To achieve earlier breast cancer detection, screening x-ray mammography is recommended by health organizations worldwide and has been estimated to decrease brea
Externí odkaz:
http://arxiv.org/abs/1912.11027
Autor:
Marinovich, M. Luke, Wylie, Elizabeth, Lotter, William, Lund, Helen, Waddell, Andrew, Madeley, Carolyn, Pereira, Gavin, Houssami, Nehmat
Publikováno v:
In eBioMedicine April 2023 90
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Deep learning approaches to breast cancer detection in mammograms have recently shown promising results. However, such models are constrained by the limited size of publicly available mammography datasets, in large part due to privacy concerns and th
Externí odkaz:
http://arxiv.org/abs/1807.08093
While deep neural networks take loose inspiration from neuroscience, it is an open question how seriously to take the analogies between artificial deep networks and biological neuronal systems. Interestingly, recent work has shown that deep convoluti
Externí odkaz:
http://arxiv.org/abs/1805.10734
Autor:
Hendrix, Nathaniel, Lowry, Kathryn P., Elmore, Joann G., Lotter, William, Sorensen, Gregory, Hsu, William, Liao, Geraldine J., Parsian, Sana, Kolb, Suzanne, Naeim, Arash, Lee, Christoph I.
Publikováno v:
In Journal of the American College of Radiology October 2022 19(10):1098-1110