-
Nicolaou S,
Kai B,
Ho S,
Su J,
Ahamed K.
Imaging of Acute Small-Bowel Obstruction.
Am J Roentgenol. 2005;185(4):1036-1044.
doi:10.2214/AJR.04.0815
-
Foster NM,
McGory ML,
Zingmond DS,
Ko CY.
Small Bowel Obstruction: A Population-Based Appraisal.
J Am Coll Surg. 2006;203(2):170-176.
doi:10.1016/j.jamcollsurg.2006.04.020
-
Rao VM,
Levin DC,
Parker L,
Frangos AJ,
Sunshine JH.
Trends in Utilization Rates of the Various Imaging Modalities in Emergency Departments: Nationwide Medicare Data From 2000 to 2008.
JACR. 2011;8:706-709.
doi:10.1016/j.jacr.2011.04.004
-
Cheng PM,
Tejura TK,
Tran KN,
Whang G.
Detection of high-grade small bowel obstruction on conventional radiography with convolutional neural networks.
Abdom Radiol. 2018;43(5):1120-1127.
doi:10.1007/s00261-017-1294-1
-
Cheng PM,
Tran KN,
Whang G,
Tejura TK.
Refining Convolutional Neural Network Detection of Small-Bowel Obstruction in Conventional Radiography.
Am J Roentgenol. November 2018:1-9.
doi:10.2214/AJR.18.20362
-
Wang X,
Peng Y,
Lu L,
Lu Z,
Bagheri M,
Summers RM.
ChestX-ray8: Hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.
In: Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition,
CVPR 2017. Vol 2017-Janua.
; 2017:3462-3471.
doi:10.1109/CVPR.2017.369
-
Rajpurkar P,
Irvin J,
Zhu K,
et al.
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning.
November 2017.
http://arxiv.org/abs/1711.05225.
Accessed January 11,
2019.
-
Titano JJ,
Badgeley M,
Schefflein J,
et al.
Automated deep-neural-network surveillance of cranial images for acute neurologic events.
Nat Med. 2018;24(9):1337-1341.
doi:10.1038/s41591-018-0147-y
-
Szegedy C,
Ioffe S,
Vanhoucke V,
Alemi A.
Inception-v4,
Inception-ResNet and the Impact of Residual Connections on Learning.
February 2016.
http://arxiv.org/abs/1602.07261.
Accessed January 11,
2019.
-
Loshchilov I,
Hutter F.
SGDR: Stochastic Gradient Descent with Warm Restarts.
August 2016.
http://arxiv.org/abs/1608.03983.
Accessed January 11,
2019.
-
Selvaraju RR,
Cogswell M,
Das A,
Vedantam R,
Parikh D,
Batra D.
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization.
In: Proceedings of the IEEE International Conference on Computer Vision. Vol 2017-Octob.
; 2017:618-626.
doi:10.1109/ICCV.2017.74
-
Goodfellow IJ,
Pouget-Abadie J,
Mirza M,
et al.
Generative Adversarial Networks.
June 2014.
http://arxiv.org/abs/1406.2661.
Accessed January 11,
2019.
-
Frid-Adar M,
Klang E,
Amitai M,
Goldberger J,
Greenspan H.
Synthetic data augmentation using GAN for improved liver lesion classification.
In: Proceedings - International Symposium on Biomedical Imaging. Vol 2018-April.
; 2018:289-293.
doi:10.1109/ISBI.2018.8363576
-
Lin TY,
Goyal P,
Girshick R,
He K,
Dollar P.
Focal Loss for Dense Object Detection.
In: Proceedings of the IEEE International Conference on Computer Vision. Vol 2017-Octob.
; 2017:2999-3007.
doi:10.1109/ICCV.2017.324