Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Alexej Gossmann"'
Autor:
Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Publikováno v:
SIAM Journal on Mathematics of Data Science. 3:692-714
Performance evaluation of continuously evolving machine learning algorithms presents new challenges, especially for high-risk application domains such as medicine. In principle, to obtain performan...
Publikováno v:
Biometrics. 77:45-48
Autor:
Mimi C Sammarco, Jennifer Simkin, Alexander J Cammack, Danielle Fassler, Alexej Gossmann, Luis Marrero, Michelle Lacey, Keith Van Meter, Ken Muneoka
Publikováno v:
PLoS ONE, Vol 10, Iss 10, p e0140156 (2015)
Oxygen is critical for optimal bone regeneration. While axolotls and salamanders have retained the ability to regenerate whole limbs, mammalian regeneration is restricted to the distal tip of the digit (P3) in mice, primates, and humans. Our previous
Externí odkaz:
https://doaj.org/article/ee60b869acaa45529983dd55a8a83cac
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA, vol 29, iss 5
J Am Med Inform Assoc
J Am Med Inform Assoc
Objective After deploying a clinical prediction model, subsequently collected data can be used to fine-tune its predictions and adapt to temporal shifts. Because model updating carries risks of over-updating/fitting, we study online methods with perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51eaa2729449b2189269de3456de1f61
Publikováno v:
Medical Imaging 2020: Computer-Aided Diagnosis.
Despite the prominent success of deep learning (DL) in medical imaging for tasks such as computer-aided detection and diagnosis, the field faces a number of challenging problems. An important issue is that of mismatch of data distributions between di
Publikováno v:
Medical Imaging: Image Perception, Observer Performance, and Technology Assessment
In this study, we show that when a training data set is supplemented by drawing samples from a distribution that is different from that of the target population, the differences in the distributions of the original and supplemental training populatio
Publikováno v:
SSCI
A novel variational inference based resampling framework is proposed to evaluate the robustness and generalization capability of deep learning models with respect to distribution shift. We use Auto Encoding Variational Bayes to find a latent represen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1139ce666853e58f5616cc39928be20a
http://arxiv.org/abs/1906.02972
http://arxiv.org/abs/1906.02972
Publikováno v:
IEEE/ACM transactions on computational biology and bioinformatics. 15(4)
The method of Sorted L-One Penalized Estimation , or SLOPE , is a sparse regression method recently introduced by Bogdan et. al. [1] . It can be used to identify significant predictor variables in a linear model that may have more unknown parameters
Publikováno v:
Medical Imaging: Image Perception, Observer Performance, and Technology Assessment
After the initial release of a machine learning algorithm, the subsequently gathered data can be used to augment the training dataset in order to modify or fine-tune the algorithm. For algorithm performance evaluation that generalizes to a targeted p