A citation-based method for searching scientific literature

Jared L Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, Yuval Kluger. BMC Med Res Methodol 2018
Times Cited: 170







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



Times Cited
  Times     Co-cited
Similarity



Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
13

Evaluating the yield of medical tests.
F E Harrell, R M Califf, D B Pryor, K L Lee, R A Rosati. JAMA 1982
13

A neural network model for survival data.
D Faraggi, R Simon. Stat Med 1995
92
13

Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.
Kumardeep Chaudhary, Olivier B Poirion, Liangqun Lu, Lana X Garmire. Clin Cancer Res 2018
291
10

A scalable discrete-time survival model for neural networks.
Michael F Gensheimer, Balasubramanian Narasimhan. PeerJ 2019
24
41

Deep learning-based survival prediction of oral cancer patients.
Dong Wook Kim, Sanghoon Lee, Sunmo Kwon, Woong Nam, In-Ho Cha, Hyung Jun Kim. Sci Rep 2019
64
15

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
Freddie Bray, Jacques Ferlay, Isabelle Soerjomataram, Rebecca L Siegel, Lindsey A Torre, Ahmedin Jemal. CA Cancer J Clin 2018
10

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.
Safoora Yousefi, Fatemeh Amrollahi, Mohamed Amgad, Chengliang Dong, Joshua E Lewis, Congzheng Song, David A Gutman, Sameer H Halani, Jose Enrique Velazquez Vega, Daniel J Brat,[...]. Sci Rep 2017
69
13

A guide to deep learning in healthcare.
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar, Volodymyr Kuleshov, Mark DePristo, Katherine Chou, Claire Cui, Greg Corrado, Sebastian Thrun, Jeff Dean. Nat Med 2019
500
8

Predicting cancer outcomes from histology and genomics using convolutional networks.
Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, Lee A D Cooper. Proc Natl Acad Sci U S A 2018
260
8

The Cancer Genome Atlas Pan-Cancer analysis project.
John N Weinstein, Eric A Collisson, Gordon B Mills, Kenna R Mills Shaw, Brad A Ozenberger, Kyle Ellrott, Ilya Shmulevich, Chris Sander, Joshua M Stuart. Nat Genet 2013
8

Support vector methods for survival analysis: a comparison between ranking and regression approaches.
Vanya Van Belle, Kristiaan Pelckmans, Sabine Van Huffel, Johan A K Suykens. Artif Intell Med 2011
38
18

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent.
Noah Simon, Jerome Friedman, Trevor Hastie, Rob Tibshirani. J Stat Softw 2011
648
7


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
6

On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data.
Hajime Uno, Tianxi Cai, Michael J Pencina, Ralph B D'Agostino, L J Wei. Stat Med 2011
621
6

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer.
Zhi Huang, Xiaohui Zhan, Shunian Xiang, Travis S Johnson, Bryan Helm, Christina Y Yu, Jie Zhang, Paul Salama, Maher Rizkalla, Zhi Han,[...]. Front Genet 2019
49
12


Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.
Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes van Diest, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen A W M van der Laak, Meyke Hermsen, Quirine F Manson, Maschenka Balkenhol,[...]. JAMA 2017
759
5

Machine learning applications in cancer prognosis and prediction.
Konstantina Kourou, Themis P Exarchos, Konstantinos P Exarchos, Michalis V Karamouzis, Dimitrios I Fotiadis. Comput Struct Biotechnol J 2014
607
5

Supervised risk predictor of breast cancer based on intrinsic subtypes.
Joel S Parker, Michael Mullins, Maggie C U Cheang, Samuel Leung, David Voduc, Tammi Vickery, Sherri Davies, Christiane Fauron, Xiaping He, Zhiyuan Hu,[...]. J Clin Oncol 2009
5

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.
Zhi Huang, Travis S Johnson, Zhi Han, Bryan Helm, Sha Cao, Chi Zhang, Paul Salama, Maher Rizkalla, Christina Y Yu, Jun Cheng,[...]. BMC Med Genomics 2020
17
29

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.
Hugo J W L Aerts, Emmanuel Rios Velazquez, Ralph T H Leijenaar, Chintan Parmar, Patrick Grossmann, Sara Carvalho, Johan Bussink, René Monshouwer, Benjamin Haibe-Kains, Derek Rietveld,[...]. Nat Commun 2014
5


The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.
Christina Curtis, Sohrab P Shah, Suet-Feung Chin, Gulisa Turashvili, Oscar M Rueda, Mark J Dunning, Doug Speed, Andy G Lynch, Shamith Samarajiwa, Yinyin Yuan,[...]. Nature 2012
5




Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma.
Hao Peng, Di Dong, Meng-Jie Fang, Lu Li, Ling-Long Tang, Lei Chen, Wen-Fei Li, Yan-Ping Mao, Wei Fan, Li-Zhi Liu,[...]. Clin Cancer Res 2019
93
4

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.
Jakob Nikolas Kather, Johannes Krisam, Pornpimol Charoentong, Tom Luedde, Esther Herpel, Cleo-Aron Weis, Timo Gaiser, Alexander Marx, Nektarios A Valous, Dyke Ferber,[...]. PLoS Med 2019
147
4

Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study.
Ahmed Hosny, Chintan Parmar, Thibaud P Coroller, Patrick Grossmann, Roman Zeleznik, Avnish Kumar, Johan Bussink, Robert J Gillies, Raymond H Mak, Hugo J W L Aerts. PLoS Med 2018
165
4

Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.
Yunlang She, Zhuochen Jin, Junqi Wu, Jiajun Deng, Lei Zhang, Hang Su, Gening Jiang, Haipeng Liu, Dong Xie, Nan Cao,[...]. JAMA Netw Open 2020
19
21

Deep learning-based classification of mesothelioma improves prediction of patient outcome.
Pierre Courtiol, Charles Maussion, Matahi Moarii, Elodie Pronier, Samuel Pilcer, Meriem Sefta, Pierre Manceron, Sylvain Toldo, Mikhail Zaslavskiy, Nolwenn Le Stang,[...]. Nat Med 2019
84
4


A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme.
Jiangwei Lao, Yinsheng Chen, Zhi-Cheng Li, Qihua Li, Ji Zhang, Jing Liu, Guangtao Zhai. Sci Rep 2017
196
4

pROC: an open-source package for R and S+ to analyze and compare ROC curves.
Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez, Markus Müller. BMC Bioinformatics 2011
4

Radiomics: the process and the challenges.
Virendra Kumar, Yuhua Gu, Satrajit Basu, Anders Berglund, Steven A Eschrich, Matthew B Schabath, Kenneth Forster, Hugo J W L Aerts, Andre Dekker, David Fenstermacher,[...]. Magn Reson Imaging 2012
947
4

Scalable and accurate deep learning with electronic health records.
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M Dai, Nissan Hajaj, Michaela Hardt, Peter J Liu, Xiaobing Liu, Jake Marcus, Mimi Sun,[...]. NPJ Digit Med 2018
581
4

External validation of a Cox prognostic model: principles and methods.
Patrick Royston, Douglas G Altman. BMC Med Res Methodol 2013
434
4

Regression modelling strategies for improved prognostic prediction.
F E Harrell, K L Lee, R M Califf, D B Pryor, R A Rosati. Stat Med 1984
4

The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge.
Katarzyna Tomczak, Patrycja Czerwińska, Maciej Wiznerowicz. Contemp Oncol (Pozn) 2015
4

Radiomics: Images Are More than Pictures, They Are Data.
Robert J Gillies, Paul E Kinahan, Hedvig Hricak. Radiology 2016
4


The Application of Deep Learning in Cancer Prognosis Prediction.
Wan Zhu, Longxiang Xie, Jianye Han, Xiangqian Guo. Cancers (Basel) 2020
46
8

From Local Explanations to Global Understanding with Explainable AI for Trees.
Scott M Lundberg, Gabriel Erion, Hugh Chen, Alex DeGrave, Jordan M Prutkin, Bala Nair, Ronit Katz, Jonathan Himmelfarb, Nisha Bansal, Su-In Lee. Nat Mach Intell 2020
364
4

Deep learning: new computational modelling techniques for genomics.
Gökcen Eraslan, Žiga Avsec, Julien Gagneur, Fabian J Theis. Nat Rev Genet 2019
264
4

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Laure Wynants, Ben Van Calster, Gary S Collins, Richard D Riley, Georg Heinze, Ewoud Schuit, Marc M J Bonten, Darren L Dahly, Johanna A A Damen, Thomas P A Debray,[...]. BMJ 2020
4

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.
Diego Ardila, Atilla P Kiraly, Sujeeth Bharadwaj, Bokyung Choi, Joshua J Reicher, Lily Peng, Daniel Tse, Mozziyar Etemadi, Wenxing Ye, Greg Corrado,[...]. Nat Med 2019
422
3

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
3


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.