Jared L Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, Yuval Kluger. BMC Med Res Methodol 2018
Times Cited: 170
Times Cited: 170
Times Cited
Times Co-cited
Similarity
Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.
Travers Ching, Xun Zhu, Lana X Garmire. PLoS Comput Biol 2018
Travers Ching, Xun Zhu, Lana X Garmire. PLoS Comput Biol 2018
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Evaluating the yield of medical tests.
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F E Harrell, R M Califf, D B Pryor, K L Lee, R A Rosati. JAMA 1982
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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
Kumardeep Chaudhary, Olivier B Poirion, Liangqun Lu, Lana X Garmire. Clin Cancer Res 2018
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A scalable discrete-time survival model for neural networks.
Michael F Gensheimer, Balasubramanian Narasimhan. PeerJ 2019
Michael F Gensheimer, Balasubramanian Narasimhan. PeerJ 2019
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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
Dong Wook Kim, Sanghoon Lee, Sunmo Kwon, Woong Nam, In-Ho Cha, Hyung Jun Kim. Sci Rep 2019
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Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
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Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.
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Andre Esteva, Alexandre Robicquet, Bharath Ramsundar, Volodymyr Kuleshov, Mark DePristo, Katherine Chou, Claire Cui, Greg Corrado, Sebastian Thrun, Jeff Dean. Nat Med 2019
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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
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The Cancer Genome Atlas Pan-Cancer analysis project.
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Dermatologist-level classification of skin cancer with deep neural networks.
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On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data.
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SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer.
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Supervised risk predictor of breast cancer based on intrinsic subtypes.
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Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.
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Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data.
Changhee Lee, Jinsung Yoon, Mihaela van der Schaar. IEEE Trans Biomed Eng 2020
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Deep learning with multimodal representation for pancancer prognosis prediction.
Anika Cheerla, Olivier Gevaert. Bioinformatics 2019
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Unbiased split variable selection for random survival forests using maximally selected rank statistics.
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Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma.
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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
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4
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4
Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.
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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
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4
Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.
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A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme.
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Radiomics: the process and the challenges.
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Scalable and accurate deep learning with electronic health records.
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The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge.
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Radiomics: Images Are More than Pictures, They Are Data.
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From Local Explanations to Global Understanding with Explainable AI for Trees.
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Deep learning: new computational modelling techniques for genomics.
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Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
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End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.
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Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
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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.