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Veronika Cheplygina

Showing results (1-10 of 16) with videos related to

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NPJ Digital Medicine|April 13, 2022
Machine learning for medical imaging: methodological failures and recommendations for the futureGaël Varoquaux, Veronika Cheplygina
IEEE Transactions on Neural Networks and Learning Systems|May 24, 2016
Dissimilarity-Based Ensembles for Multiple Instance LearningVeronika Cheplygina, David M J Tax, Marco Loog
Proceedings of Spie--The International Society for Optical Engineering|June 27, 2025
Exploring connections of spectral analysis and transfer learning in medical imagingYucheng Lu, Dovile Juodelyte, Jonathan D Victor, et al.
Medical Image Analysis|April 9, 2019
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysisVeronika Cheplygina, Marleen de Bruijne, Josien P W Pluim
Plos Computational Biology|February 11, 2020
Ten simple rules for getting started on Twitter as a scientistVeronika Cheplygina, Felienne Hermans, Casper Albers, et al.
BMC Research Notes|September 10, 2024
A grassroots approach to peer support by the Danish Reproducibility NetworkMarta Topor, Philippe Bonnet, Veronika Cheplygina, et al.
Plos Computational Biology|December 15, 2022
Ten simple rules for failing successfully in academiaStefan Gaillard, Tara van Viegen, Michele Veldsman, et al.
Journal of Imaging Informatics in Medicine|May 20, 2025
Mask of Truth: Model Sensitivity to Unexpected Regions of Medical ImagesThéo Sourget, Michelle Hestbek-Møller, Amelia Jiménez-Sánchez, et al.
Plos One|April 22, 2021
Crowdsourcing airway annotations in chest computed tomography imagesVeronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, et al.
IEEE Journal of Biomedical and Health Informatics|July 11, 2018
Transfer Learning for Multicenter Classification of Chronic Obstructive Pulmonary DiseaseVeronika Cheplygina, Isabel Pino Pena, Jesper Holst Pedersen, et al.
Pageof 2

Showing results (1-10 of 16) with videos related to

Sort By:
Pageof 2
NPJ Digital Medicine|April 13, 2022
Machine learning for medical imaging: methodological failures and recommendations for the futureGaël Varoquaux, Veronika Cheplygina
IEEE Transactions on Neural Networks and Learning Systems|May 24, 2016
Dissimilarity-Based Ensembles for Multiple Instance LearningVeronika Cheplygina, David M J Tax, Marco Loog
Proceedings of Spie--The International Society for Optical Engineering|June 27, 2025
Exploring connections of spectral analysis and transfer learning in medical imagingYucheng Lu, Dovile Juodelyte, Jonathan D Victor, et al.
Medical Image Analysis|April 9, 2019
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysisVeronika Cheplygina, Marleen de Bruijne, Josien P W Pluim
Plos Computational Biology|February 11, 2020
Ten simple rules for getting started on Twitter as a scientistVeronika Cheplygina, Felienne Hermans, Casper Albers, et al.
BMC Research Notes|September 10, 2024
A grassroots approach to peer support by the Danish Reproducibility NetworkMarta Topor, Philippe Bonnet, Veronika Cheplygina, et al.
Plos Computational Biology|December 15, 2022
Ten simple rules for failing successfully in academiaStefan Gaillard, Tara van Viegen, Michele Veldsman, et al.
Journal of Imaging Informatics in Medicine|May 20, 2025
Mask of Truth: Model Sensitivity to Unexpected Regions of Medical ImagesThéo Sourget, Michelle Hestbek-Møller, Amelia Jiménez-Sánchez, et al.
Plos One|April 22, 2021
Crowdsourcing airway annotations in chest computed tomography imagesVeronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, et al.
IEEE Journal of Biomedical and Health Informatics|July 11, 2018
Transfer Learning for Multicenter Classification of Chronic Obstructive Pulmonary DiseaseVeronika Cheplygina, Isabel Pino Pena, Jesper Holst Pedersen, et al.
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