A citation-based method for searching scientific literature


List of co-cited articles
226 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
30

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
19


Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
17

A survey on deep learning in medical image analysis.
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A W M van der Laak, Bram van Ginneken, Clara I Sánchez. Med Image Anal 2017
14

Performance-optimized hierarchical models predict neural responses in higher visual cortex.
Daniel L K Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, James J DiCarlo. Proc Natl Acad Sci U S A 2014
414
12

A fast learning algorithm for deep belief nets.
Geoffrey E Hinton, Simon Osindero, Yee-Whye Teh. Neural Comput 2006
11

Reducing the dimensionality of data with neural networks.
G E Hinton, R R Salakhutdinov. Science 2006
10

Mastering the game of Go with deep neural networks and tree search.
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot,[...]. Nature 2016
824
9


Dermatologist-level classification of skin cancer with deep neural networks.
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, Sebastian Thrun. Nature 2017
9



Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
7

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
7



Deep Learning in Medical Image Analysis.
Dinggang Shen, Guorong Wu, Heung-Il Suk. Annu Rev Biomed Eng 2017
637
5

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network.
Marios Anthimopoulos, Stergios Christodoulidis, Lukas Ebner, Andreas Christe, Stavroula Mougiakakou. IEEE Trans Med Imaging 2016
210
5

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
5

Seeing it all: Convolutional network layers map the function of the human visual system.
Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion. Neuroimage 2017
56
8

Convolutional Neural Networks for Radiologic Images: A Radiologist's Guide.
Shelly Soffer, Avi Ben-Cohen, Orit Shimon, Michal Marianne Amitai, Hayit Greenspan, Eyal Klang. Radiology 2019
89
5

Artificial convolution neural network techniques and applications for lung nodule detection.
S B Lo, S A Lou, J S Lin, M T Freedman, M V Chien, S K Mun. IEEE Trans Med Imaging 1995
75
6

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
512
5


Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.
Hoo-Chang Shin, Holger R Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura, Ronald M Summers. IEEE Trans Med Imaging 2016
701
5

Human-level control through deep reinforcement learning.
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski,[...]. Nature 2015
722
4

Representation learning: a review and new perspectives.
Yoshua Bengio, Aaron Courville, Pascal Vincent. IEEE Trans Pattern Anal Mach Intell 2013
761
4

Deep Learning: The Good, the Bad, and the Ugly.
Thomas Serre. Annu Rev Vis Sci 2019
24
16


A deep learning framework for neuroscience.
Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli,[...]. Nat Neurosci 2019
73
5

Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
136
4

Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.
Saeed Reza Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier. Sci Rep 2016
46
8

Deep convolutional models improve predictions of macaque V1 responses to natural images.
Santiago A Cadena, George H Denfield, Edgar Y Walker, Leon A Gatys, Andreas S Tolias, Matthias Bethge, Alexander S Ecker. PLoS Comput Biol 2019
31
12

Image Super-Resolution Using Deep Convolutional Networks.
Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. IEEE Trans Pattern Anal Mach Intell 2016
335
4

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros,[...]. JAMA 2016
4

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
154
4

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
140
4

Deep Learning in Medical Imaging: General Overview.
June-Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee, Guk Bae Kim, Joon Beom Seo, Namkug Kim. Korean J Radiol 2017
198
3

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, Jae Y Shin, Suryakanth R Gurudu, R Todd Hurst, Christopher B Kendall, Michael B Gotway, Jianming Liang. IEEE Trans Med Imaging 2016
406
3

Overview of deep learning in medical imaging.
Kenji Suzuki. Radiol Phys Technol 2017
148
3

Highly accurate model for prediction of lung nodule malignancy with CT scans.
Jason L Causey, Junyu Zhang, Shiqian Ma, Bo Jiang, Jake A Qualls, David G Politte, Fred Prior, Shuzhong Zhang, Xiuzhen Huang. Sci Rep 2018
46
6

Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images.
B Sahiner, H P Chan, N Petrick, D Wei, M A Helvie, D D Adler, M M Goodsitt. IEEE Trans Med Imaging 1996
118
3

Computer-aided classification of lung nodules on computed tomography images via deep learning technique.
Kai-Lung Hua, Che-Hao Hsu, Shintami Chusnul Hidayati, Wen-Huang Cheng, Yu-Jen Chen. Onco Targets Ther 2015
99
3

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks.
Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Geert Litjens, Paul Gerke, Colin Jacobs, Sarah J van Riel, Mathilde Marie Winkler Wille, Matiullah Naqibullah, Clara I Sanchez, Bram van Ginneken. IEEE Trans Med Imaging 2016
232
3


Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.
Geert Litjens, Clara I Sánchez, Nadya Timofeeva, Meyke Hermsen, Iris Nagtegaal, Iringo Kovacs, Christina Hulsbergen-van de Kaa, Peter Bult, Bram van Ginneken, Jeroen van der Laak. Sci Rep 2016
257
3

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.
Dharshan Kumaran, Demis Hassabis, James L McClelland. Trends Cogn Sci 2016
108
3

Convolutional neural network-based encoding and decoding of visual object recognition in space and time.
K Seeliger, M Fritsche, U Güçlü, S Schoenmakers, J-M Schoffelen, S E Bosch, M A J van Gerven. Neuroimage 2018
26
11

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
33
9


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.