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Recent advances in deep learning and computer vision have reduced many barriers to automated medical image analysis, allowing algorithms to process label-free images and improve performance.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2002
Earlier work this paper cites.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton · 2002
Earlier work this paper cites.
Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altch’e, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, and Michal Valko · 2006
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The world incidence and prevalence of autoimmune diseases is increasing
Aaron Lerner, Patricia Jeremias, and Torsten Matthias · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Dermofit project datasets
Robert Fisher and Jonathan Rees · 2017
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brain tumor dataset
Jun Cheng · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross B. Girshick, Kaiming He, and Piotr Dollár · 2017
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The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
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Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic)
David A. Gutman, Noel C. F. Codella, M. E. Celebi, Brian Helba, Michael Armando Marchetti, Nabin K. Mishra, and Allan C. Halpern · 2018
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Averaging weights leads to wider optima and better generalization
Pavel Izmailov, Dmitrii Podoprikhin, T. Garipov, Dmitry P. Vetrov, and Andrew Gordon Wilson · 2018
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Bcn20000: Dermoscopic lesions in the wild
Marc Combalia, Noel C. F. Codella, Veronica M Rotemberg, Brian Helba, Verónica Vilaplana, Ofer Reiter, Allan C. Halpern, Susana Puig, and Josep Malvehy · 2019
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Deep convolutional neural network based medical image classification for disease diagnosis
Samir S Yadav and Shivajirao M Jadhav · 2019
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Using self-supervised learning can improve model robustness and uncertainty
Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, and Dawn Song · 2019
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Pytorch image models
Ross Wightman · 2019
Cited alongside, same era.
Transfusion: Understanding transfer learning for medical imaging
Maithra Raghu, Chiyuan Zhang, Jon Kleinberg, and Samy Bengio · 2019
Cited alongside, same era.
Autoimmune and inflammatory diseases following covid-19
Caroline Galeotti and Jagadeesh Bayry · 2020
Cited alongside, same era.
Covid-19 and autoimmunity
Michael Ehrenfeld, Angela Tincani, Laura Andreoli, Marco Cattalini, Assaf Greenbaum, Darja Kanduc, Jaume Alijotas-Reig, Vsevolod Zinserling, Natalia Semenova, Howard Amital, et al · 2020
Cited alongside, same era.
A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases
I. S. Stafford, M Kellermann, E Mossotto, Robert Mark Beattie, Ben D. MacArthur, and Sarah Ennis · 2020
Cited alongside, same era.
A survey of the recent architectures of deep convolutional neural networks
Asifullah Khan, Anabia Sohail, Umme Zahoora, and Aqsa Saeed Qureshi · 2020
Training data-efficient image transformers & amp; distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Herve Jegou · 2021
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Convit: Improving vision transformers with soft convolutional inductive biases
Stéphane d’Ascoli, Hugo Touvron, Matthew Leavitt, Ari Morcos, Giulio Biroli, and Levent Sagun · 2021
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Is it time to replace cnns with transformers for medical images?
Christos Matsoukas, Johan Fredin Haslum, Magnus P Soderberg, and Kevin Smith · 2021
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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Do vision transformers see like convolutional neural networks?
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, and Alexey Dosovitskiy · 2021
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Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Bootstrap your own latent - a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, koray kavukcuoglu, Remi Munos, and Michal Valko · 2020
Cited alongside, same era.
Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
Cited alongside, same era.
Covid-19 and autoimmune diseases
Yu Liu, Amr H. Sawalha, and Qianjin Lu · 2020
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick · 2020
Cited alongside, same era.
Skin lesion classification using ensembles of multi-resolution efficientnets with meta data
Nils Gessert, Maximilian Nielsen, Mohsin Shaikh, René Werner, and A. Schlaefer · 2020
Cited alongside, same era.
Knowledge distillation: A survey
Jianping Gou, Baosheng Yu, Stephen J Maybank, and Dacheng Tao · 2021
Later among the works it cites.
David Picard · 2021
Later among the works it cites.
Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
Later among the works it cites.
Masked autoencoders are scalable vision learners. corr abs/2111.06377 (2021)
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross B Girshick · 2021
Later among the works it cites.
Computer vision in autoimmune diseases diagnosis—current status and perspectives
Viktoria N Tsakalidou, Pavlina Mitsou, and George A Papakostas · 2022
Closest in time.
Pranav Singh and Jacopo Cirrone · 2022
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Self-supervised learning from 100 million medical images
Florin C Ghesu, Bogdan Georgescu, Awais Mansoor, Youngjin Yoo, Dominik Neumann, Pragneshkumar Patel, RS Vishwanath, James M Balter, Yue Cao, Sasa Grbic, et al · 2022
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Cmkd: Cnn/transformer-based cross-model knowledge distillation for audio classification
Yuan Gong, Sameer Khurana, Andrew Rouditchenko, and James R. Glass · 2022
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Artificial intelligence and deep learning to map immune cell types in inflamed human tissue
Kayla Van Buren, Yi Li, Fanghao Zhong, Yuan Ding, Amrutesh Puranik, Cynthia A. Loomis, Narges Razavian, and Timothy B. Niewold · 2022
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A new model for brain tumor detection using ensemble transfer learning and quantum variational classifier
Javeria Amin, Muhammad Almas Anjum, Muhammad Sharif, Saima Jabeen, Seifedine Kadry, and Pablo Moreno Ger · 2022
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Analysis of the isic image datasets: usage, benchmarks and recommendations
Bill Cassidy, Connah Kendrick, Andrzej Brodzicki, Joanna Jaworek-Korjakowska, and Moi Hoon Yap · 2022
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