Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
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P. Baldi | G. Urban | Priya Tripathi | T. Alkayali | Mohit Mittal | F. Jalali | W. Karnes
[1] Pierre Baldi,et al. Neural Networks for Fingerprint Recognition , 1993, Neural Computation.
[2] A. Zauber,et al. Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. , 1993 .
[3] Pierre Baldi,et al. Assessing the accuracy of prediction algorithms for classification: an overview , 2000, Bioinform..
[4] Shinji Tanaka,et al. Nonpolypoid (flat and depressed) colorectal neoplasms. , 2006, Gastroenterology.
[5] Lin Wu,et al. Learning to play Go using recursive neural networks , 2008, Neural Networks.
[6] H. Pohl,et al. Colorectal cancers detected after colonoscopy frequently result from missed lesions. , 2010, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.
[7] Iris Lansdorp-Vogelaar,et al. A Systematic Comparison of Microsimulation Models of Colorectal Cancer , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.
[8] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[9] Fernando Vilariño,et al. Towards automatic polyp detection with a polyp appearance model , 2012, Pattern Recognit..
[10] Pierre Baldi,et al. Deep architectures for protein contact map prediction , 2012, Bioinform..
[11] A. M. Leufkens,et al. Factors influencing the miss rate of polyps in a back-to-back colonoscopy study , 2012, Endoscopy.
[12] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[13] Andrew Zisserman,et al. Return of the Devil in the Details: Delving Deep into Convolutional Nets , 2014, BMVC.
[14] Pierre Baldi,et al. The dropout learning algorithm , 2014, Artif. Intell..
[15] G. Heinze,et al. Endoscopists with low adenoma detection rates benefit from high-definition endoscopy , 2015, Surgical Endoscopy.
[16] P. Baldi,et al. Searching for exotic particles in high-energy physics with deep learning , 2014, Nature Communications.
[17] Swati G. Patel,et al. Prevention of interval colorectal cancers: what every clinician needs to know. , 2014, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.
[18] Christopher D. Jensen,et al. Adenoma detection rate and risk of colorectal cancer and death. , 2014, The New England journal of medicine.
[19] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[20] A. Saklani,et al. Diagnostic miss rate for colorectal cancer: an audit , 2015, Annals of gastroenterology : quarterly publication of the Hellenic Society of Gastroenterology.
[21] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[22] Joseph C Anderson,et al. Colonoscopy: Quality Indicators , 2015, Clinical and Translational Gastroenterology.
[23] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[24] A. Bond,et al. New technologies and techniques to improve adenoma detection in colonoscopy. , 2015, World journal of gastrointestinal endoscopy.
[25] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[27] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[28] W. Strum. Colorectal Adenomas. , 2016, The New England journal of medicine.
[29] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Sun Young Park,et al. Colonoscopic polyp detection using convolutional neural networks , 2016, SPIE Medical Imaging.
[31] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[33] George Kurian,et al. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation , 2016, ArXiv.
[34] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Andreas Uhl,et al. Colonic Polyp Classification with Convolutional Neural Networks , 2016, 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS).
[36] Sabee Molloi,et al. Detecting Cardiovascular Disease from Mammograms With Deep Learning , 2017, IEEE Transactions on Medical Imaging.
[37] Min-Ying Su,et al. A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks , 2017, Comput. Biol. Medicine.
[38] Paulina Wieszczy,et al. Increased Rate of Adenoma Detection Associates With Reduced Risk of Colorectal Cancer and Death. , 2017, Gastroenterology.
[39] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[40] Pierre Baldi,et al. Decorrelated jet substructure tagging using adversarial neural networks , 2017, Physical Review D.
[41] C. Hassan,et al. Full-spectrum (FUSE) versus standard forward-viewing colonoscopy in an organised colorectal cancer screening programme , 2016, Gut.
[42] Aymeric Histace,et al. Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge , 2017, IEEE Transactions on Medical Imaging.
[43] P. Baldi,et al. Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas , 2018, American Journal of Neuroradiology.
[44] Pierre Baldi,et al. Deep Learning in Biomedical Data Science , 2018, Annual Review of Biomedical Data Science.
[45] Gregor Urban,et al. Deep learning for chemical reaction prediction , 2018 .