A citation-based method for searching scientific literature

S Hochreiter, J Schmidhuber. Neural Comput 1997
Times Cited: 5103







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



Times Cited
  Times     Co-cited
Similarity


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
8

LSTM: A Search Space Odyssey.
Klaus Greff, Rupesh K Srivastava, Jan Koutnik, Bas R Steunebrink, Jurgen Schmidhuber. IEEE Trans Neural Netw Learn Syst 2017
390
7

Learning long-term dependencies with gradient descent is difficult.
Y Bengio, P Simard, P Frasconi. IEEE Trans Neural Netw 1994
621
7

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
5

Learning to forget: continual prediction with LSTM.
F A Gers, J Schmidhuber, F Cummins. Neural Comput 2000
387
5

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.
Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun. IEEE Trans Pattern Anal Mach Intell 2017
4

BioBERT: a pre-trained biomedical language representation model for biomedical text mining.
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, Jaewoo Kang. Bioinformatics 2020
585
4

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.
Awni Y Hannun, Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H Tison, Codie Bourn, Mintu P Turakhia, Andrew Y Ng. Nat Med 2019
588
3

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.
Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov,[...]. Front Pharmacol 2020
89
3

Deep reinforcement learning for de novo drug design.
Mariya Popova, Olexandr Isayev, Alexander Tropsha. Sci Adv 2018
320
3

Time series forecasting of COVID-19 transmission in Canada using LSTM networks.
Vinay Kumar Reddy Chimmula, Lei Zhang. Chaos Solitons Fractals 2020
224
3

An Experimental Review on Deep Learning Architectures for Time Series Forecasting.
Pedro Lara-Benítez, Manuel Carranza-García, José C Riquelme. Int J Neural Syst 2021
22
13


Highly accurate protein structure prediction with AlphaFold.
John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko,[...]. Nature 2021
3

PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.
A L Goldberger, L A Amaral, L Glass, J M Hausdorff, P C Ivanov, R G Mark, J E Mietus, G B Moody, C K Peng, H E Stanley. Circulation 2000
3

Image quality assessment: from error visibility to structural similarity.
Zhou Wang, Alan Conrad Bovik, Hamid Rahim Sheikh, Eero P Simoncelli. IEEE Trans Image Process 2004
2

Re-visiting the echo state property.
Izzet B Yildiz, Herbert Jaeger, Stefan J Kiebel. Neural Netw 2012
66
3

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach.
Jaideep Pathak, Brian Hunt, Michelle Girvan, Zhixin Lu, Edward Ott. Phys Rev Lett 2018
193
2

Covid-19 - Navigating the Uncharted.
Anthony S Fauci, H Clifford Lane, Robert R Redfield. N Engl J Med 2020
841
2

LSTM-Based ECG Classification for Continuous Monitoring on Personal Wearable Devices.
Saeed Saadatnejad, Mohammadhosein Oveisi, Matin Hashemi. IEEE J Biomed Health Inform 2020
63
3

Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks.
Serkan Kiranyaz, Turker Ince, Moncef Gabbouj. IEEE Trans Biomed Eng 2016
293
2

Detecting atrial fibrillation by deep convolutional neural networks.
Yong Xia, Naren Wulan, Kuanquan Wang, Henggui Zhang. Comput Biol Med 2018
81
2

The impact of the MIT-BIH arrhythmia database.
G B Moody, R G Mark. IEEE Eng Med Biol Mag 2001
577
2


Reinforced Adversarial Neural Computer for de Novo Molecular Design.
Evgeny Putin, Arip Asadulaev, Yan Ivanenkov, Vladimir Aladinskiy, Benjamin Sanchez-Lengeling, Alán Aspuru-Guzik, Alex Zhavoronkov. J Chem Inf Model 2018
119
2

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks.
Marwin H S Segler, Thierry Kogej, Christian Tyrchan, Mark P Waller. ACS Cent Sci 2018
405
2

Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development.
Arash Keshavarzi Arshadi, Julia Webb, Milad Salem, Emmanuel Cruz, Stacie Calad-Thomson, Niloofar Ghadirian, Jennifer Collins, Elena Diez-Cecilia, Brendan Kelly, Hani Goodarzi,[...]. Front Artif Intell 2020
62
3

Molecular de-novo design through deep reinforcement learning.
Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen. J Cheminform 2017
295
2


Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions.
Zifeng Yang, Zhiqi Zeng, Ke Wang, Sook-San Wong, Wenhua Liang, Mark Zanin, Peng Liu, Xudong Cao, Zhongqiang Gao, Zhitong Mai,[...]. J Thorac Dis 2020
452
2

Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM.
Farah Shahid, Aneela Zameer, Muhammad Muneeb. Chaos Solitons Fractals 2020
83
2

An interactive web-based dashboard to track COVID-19 in real time.
Ensheng Dong, Hongru Du, Lauren Gardner. Lancet Infect Dis 2020
2

The ChEMBL database in 2017.
Anna Gaulton, Anne Hersey, Michał Nowotka, A Patrícia Bento, Jon Chambers, David Mendez, Prudence Mutowo, Francis Atkinson, Louisa J Bellis, Elena Cibrián-Uhalte,[...]. Nucleic Acids Res 2017
984
2


AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning.
Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist, Esben Bjerrum. J Cheminform 2020
44
4

Large scale deep learning for computer aided detection of mammographic lesions.
Thijs Kooi, Geert Litjens, Bram van Ginneken, Albert Gubern-Mérida, Clara I Sánchez, Ritse Mann, Ard den Heeten, Nico Karssemeijer. Med Image Anal 2017
312
2

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery.
Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer. J Chem Inf Model 2018
63
3

Hybrid computing using a neural network with dynamic external memory.
Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio Gómez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou,[...]. Nature 2016
133
2

A survey of word embeddings for clinical text.
Faiza Khan Khattak, Serena Jeblee, Chloé Pou-Prom, Mohamed Abdalla, Christopher Meaney, Frank Rudzicz. J Biomed Inform 2019
27
7

Natural language processing: an introduction.
Prakash M Nadkarni, Lucila Ohno-Machado, Wendy W Chapman. J Am Med Inform Assoc 2011
311
2

fNIRS-based brain-computer interfaces: a review.
Noman Naseer, Keum-Shik Hong. Front Hum Neurosci 2015
316
2

Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders.
Orestis Tsinalis, Paul M Matthews, Yike Guo. Ann Biomed Eng 2016
80
2

Supervised methods for detection and segmentation of tissues in clinical lumbar MRI.
Subarna Ghosh, Vipin Chaudhary. Comput Med Imaging Graph 2014
18
11


Deep learning: new computational modelling techniques for genomics.
Gökcen Eraslan, Žiga Avsec, Julien Gagneur, Fabian J Theis. Nat Rev Genet 2019
325
2


Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
David Moher, Larissa Shamseer, Mike Clarke, Davina Ghersi, Alessandro Liberati, Mark Petticrew, Paul Shekelle, Lesley A Stewart. Syst Rev 2015
2

Representation learning: a review and new perspectives.
Yoshua Bengio, Aaron Courville, Pascal Vincent. IEEE Trans Pattern Anal Mach Intell 2013
2

N4ITK: improved N3 bias correction.
Nicholas J Tustison, Brian B Avants, Philip A Cook, Yuanjie Zheng, Alexander Egan, Paul A Yushkevich, James C Gee. IEEE Trans Med Imaging 2010
2

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
2


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.