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Witali Aswolinskiy

Showing results (1-10 of 11) with videos related to

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Frontiers in Computational Neuroscience|April 9, 2015
RM-SORN: a reward-modulated self-organizing recurrent neural networkWitali Aswolinskiy, Gordon Pipa
Nature Communications|May 15, 2026
Analysis of computational tumor-infiltrating lymphocytes in breast cancer from the results of the TIGER challengeMart van Rijthoven, Witali Aswolinskiy, Leslie Tessier, et al.
Medical Image Analysis|July 12, 2023
Gigapixel end-to-end training using streaming and attentionStephan Dooper, Hans Pinckaers, Witali Aswolinskiy, et al.
Medical Image Analysis|January 9, 2024
Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learningDaan J Geijs, Stephan Dooper, Witali Aswolinskiy, et al.
Journal of Pathology Informatics|May 25, 2026
Fast organ-of-origin classification for digital pathology quality controlWitali Aswolinskiy, John K L Wong, Myroslav Zapukhlyak, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|June 25, 2025
Attention-Based Whole-Slide Image Compression Achieves Pathologist-Level Prescreening of Multiorgan Routine Histopathology BiopsiesWitali Aswolinskiy, Rachel S van der Post, Michela Campora, et al.
Journal of Pathology Informatics|March 19, 2026
Diversity over scale: Whole-slide image variety enables H&E foundation model training with fewer patchesChristoph Bosch, John K L Wong, Martin Paulikat, et al.
Breast Cancer Research : BCR|November 14, 2023
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learningWitali Aswolinskiy, Enrico Munari, Hugo M Horlings, et al.
BJS Open|October 29, 2024
Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysisDiederik J Höppener, Witali Aswolinskiy, Zhen Qian, et al.
NPJ Digital Medicine|July 22, 2022
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotationsNiccolò Marini, Stefano Marchesin, Sebastian Otálora, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Frontiers in Computational Neuroscience|April 9, 2015
RM-SORN: a reward-modulated self-organizing recurrent neural networkWitali Aswolinskiy, Gordon Pipa
Nature Communications|May 15, 2026
Analysis of computational tumor-infiltrating lymphocytes in breast cancer from the results of the TIGER challengeMart van Rijthoven, Witali Aswolinskiy, Leslie Tessier, et al.
Medical Image Analysis|July 12, 2023
Gigapixel end-to-end training using streaming and attentionStephan Dooper, Hans Pinckaers, Witali Aswolinskiy, et al.
Medical Image Analysis|January 9, 2024
Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learningDaan J Geijs, Stephan Dooper, Witali Aswolinskiy, et al.
Journal of Pathology Informatics|May 25, 2026
Fast organ-of-origin classification for digital pathology quality controlWitali Aswolinskiy, John K L Wong, Myroslav Zapukhlyak, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|June 25, 2025
Attention-Based Whole-Slide Image Compression Achieves Pathologist-Level Prescreening of Multiorgan Routine Histopathology BiopsiesWitali Aswolinskiy, Rachel S van der Post, Michela Campora, et al.
Journal of Pathology Informatics|March 19, 2026
Diversity over scale: Whole-slide image variety enables H&E foundation model training with fewer patchesChristoph Bosch, John K L Wong, Martin Paulikat, et al.
Breast Cancer Research : BCR|November 14, 2023
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learningWitali Aswolinskiy, Enrico Munari, Hugo M Horlings, et al.
BJS Open|October 29, 2024
Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysisDiederik J Höppener, Witali Aswolinskiy, Zhen Qian, et al.
NPJ Digital Medicine|July 22, 2022
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotationsNiccolò Marini, Stefano Marchesin, Sebastian Otálora, et al.
Pageof 2