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International Journal of Environmental Research and Public Health.2018;10882(8)903
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106Artificial intelligence in radiology
Ahmed Hosny,Chintan Parmar,John Quackenbush,Lawrence H. Schwartz,Hugo J. W. L. Aerts
Nature Reviews Cancer.2018;18(8)500
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107Artificial intelligence in radiology
Rucha Tambe,Sarang Mahajan,Urmil Shah,Mohit Agrawal,Bhushan Garware
Nature Reviews Cancer.2019;18(8)143
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108A deep learning method for classifying mammographic breast density categories
Aly A. Mohamed,Wendie A. Berg,Hong Peng,Yahong Luo,Rachel C. Jankowitz,Shandong Wu
Medical Physics.2018;45(1)314
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109Predicting 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
Proceedings of the National Academy of Sciences.2018;115(13)E2970
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110Multi-tissue and multi-scale approach for nuclei segmentation in H&E stained images
Massimo Salvi,Filippo Molinari
BioMedical Engineering OnLine.2018;17(1)E2970
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111Discovering anomalous patterns in large digital pathology images
Sriram Somanchi,Daniel B. Neill,Anil V. Parwani
Statistics in Medicine.2018;37(25)3599
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112Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features
Germán Corredor,Jon Whitney,Viviana Arias,Anant Madabhushi,Eduardo Romero
Journal of Medical Imaging.2017;4(2)021105
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113Fluorescence-based quantification of nucleocytoplasmic transport
Joshua B. Kelley,Bryce M. Paschal
Methods.2019;157(2)106
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114Bringing 3D tumor models to the clinic - predictive value for personalized medicine
Kathrin Halfter,Barbara Mayer
Biotechnology Journal.2017;12(2)1600295
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