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107Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
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108Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer
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109Automatic cellularity assessment from post-treated breast surgical specimens
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110Automatic cellularity assessment from post-treated breast surgical specimens
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111Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks
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112Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks
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115Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks
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118COUNTERPOINT: Is ICD-10 Diagnosis Coding Important in the Era of Big Data? No
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119Advances in the computational and molecular understanding of the prostate cancer cell nucleus
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120Machine Learning and Veterinary Pathology: Be Not Afraid!
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121Prediction of BAP1 Expression in Uveal Melanoma Using Densely-Connected Deep Classification Networks
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122High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection
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123Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data
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International Journal of Computer Assisted Radiology and Surgery.2019;14(4)587
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124A Nuclei Segmentation Research Based on Convolutional Neural Network
?? ?
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125A Nuclei Segmentation Research Based on Convolutional Neural Network
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126Role of deep learning in infant brain MRI analysis
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Magnetic Resonance Imaging.2019;08(11)924
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127An Ensemble Approach for Classification of Breast Histopathology Images
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IETE Journal of Research.2019;08(11)1
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128Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images
Wenyuan Li,Jiayun Li,Karthik V. Sarma,King Chung Ho,Shiwen Shen,Beatrice S. Knudsen,Arkadiusz Gertych,Corey W. Arnold
IEEE Transactions on Medical Imaging.2019;38(4)945
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129Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images
Srishti Gautam,Arnav Bhavsar,Anil K. Sao,Harinarayan K.K.,Metin N. Gurcan,John E. Tomaszewski
IEEE Transactions on Medical Imaging.2018;38(4)32
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130Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images
Santiago López-Tapia,Cristobal Olivencia,José Aneiros-Fernández,Nicolás Pérez de la Blanca
IEEE Transactions on Medical Imaging.2019;11435(4)144
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131Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images
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132Artificial Intelligence in Pathology
Hye Yoon Chang,Chan Kwon Jung,Junwoo Isaac Woo,Sanghun Lee,Joonyoung Cho,Sun Woo Kim,Tae-Yeong Kwak
Journal of Pathology and Translational Medicine.2019;53(1)1
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133A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence–Powered Ultrasound for Improving Clinical Workflow
Zeynettin Akkus,Jason Cai,Arunnit Boonrod,Atefeh Zeinoddini,Alexander D. Weston,Kenneth A. Philbrick,Bradley J. Erickson
Journal of the American College of Radiology.2019;16(9)1318
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134A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
Neeraj Kumar,Ruchika Verma,Sanuj Sharma,Surabhi Bhargava,Abhishek Vahadane,Amit Sethi
IEEE Transactions on Medical Imaging.2017;36(7)1550
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135A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
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IEEE Transactions on Medical Imaging.2017;36(7)1
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136A survey on deep learning in medical image analysis
Geert Litjens,Thijs Kooi,Babak Ehteshami Bejnordi,Arnaud Arindra Adiyoso Setio,Francesco Ciompi,Mohsen Ghafoorian,Jeroen A.W.M. van der Laak,Bram van Ginneken,Clara I. Sánchez
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137A Review of Intrinsic Optical Imaging Serial Blockface Histology (ICI-SBH) for Whole Rodent Brain Imaging
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Photonics.2019;6(2)66
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138Deep Learning With Sampling in Colon Cancer Histology
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Frontiers in Bioengineering and Biotechnology.2019;7(2)66
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139Deep Learning With Sampling in Colon Cancer Histology
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Frontiers in Bioengineering and Biotechnology.2018;10882(2)727
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140The Job Market Outlook for Residency Graduates: Clear Weather Ahead for the Butterflies?
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141The Job Market Outlook for Residency Graduates: Clear Weather Ahead for the Butterflies?
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Archives of Pathology & Laboratory Medicine.2019;142(4)7212
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142Machine Learning Methods for Histopathological Image Analysis
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Computational and Structural Biotechnology Journal.2018;16(4)34
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143Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors
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144Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides
Arkadiusz Gertych,Zaneta Swiderska-Chadaj,Zhaoxuan Ma,Nathan Ing,Tomasz Markiewicz,Szczepan Cierniak,Hootan Salemi,Samuel Guzman,Ann E. Walts,Beatrice S. Knudsen
Scientific Reports.2019;9(1)34
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145Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides
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146Automating the Paris System for urine cytopathology—A hybrid deep-learning and morphometric approach
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147Automating the Paris System for urine cytopathology—A hybrid deep-learning and morphometric approach
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148Automatic grading of prostate cancer in digitized histopathology images: Learning from multiple experts
Guy Nir,Soheil Hor,Davood Karimi,Ladan Fazli,Brian F. Skinnider,Peyman Tavassoli,Dmitry Turbin,Carlos F. Villamil,Gang Wang,R. Storey Wilson,Kenneth A. Iczkowski,M. Scott Lucia,Peter C. Black,Purang Abolmaesumi,S. Larry Goldenberg,Septimiu E. Salcudean
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149Panoptic View of Prognostic Models for Personalized Breast Cancer Management
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150Panoptic View of Prognostic Models for Personalized Breast Cancer Management
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151Panoptic View of Prognostic Models for Personalized Breast Cancer Management
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152Survey of deep learning in breast cancer image analysis
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153A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers
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154Artificial intelligence and its potential in oncology
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155Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape
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Journal of the American Society of Cytopathology.2019;8(4)230
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156Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape
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Journal of the American Society of Cytopathology.2017;8(4)2154
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157Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software
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Virchows Archiv.2018;472(2)259
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158Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software
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159Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software
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Virchows Archiv.2019;199(2)149
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160Stacked sparse autoencoder and case-based postprocessing method for nucleus detection
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Neurocomputing.2019;359(2)494
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161Beyond the microscope: interpreting renal biopsy findings in the era of precision medicine
Serena M. Bagnasco
American Journal of Physiology-Renal Physiology.2018;315(6)F1652
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162Beyond the microscope: interpreting renal biopsy findings in the era of precision medicine
Francisco Perdigon Romero,An Tang,Samuel Kadoury
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163Machine learning and feature selection for drug response prediction in precision oncology applications
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Biophysical Reviews.2019;11(1)31
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164Impact of pre-analytical variables on deep learning accuracy in histopathology
Andrew D Jones,John Paul Graff,Morgan Darrow,Alexander Borowsky,Kristin A Olson,Regina Gandour-Edwards,Ananya Datta Mitra,Dongguang Wei,Guofeng Gao,Blythe Durbin-Johnson,Hooman H Rashidi
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165Impact of pre-analytical variables on deep learning accuracy in histopathology
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166Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring
Michelle A. Wood-Trageser,Andrew J. Lesniak,Anthony J. Demetris
Transplantation.2019;103(7)1306
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167Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Kaustav Bera,Kurt A. Schalper,David L. Rimm,Vamsidhar Velcheti,Anant Madabhushi
Nature Reviews Clinical Oncology.2019;16(11)703
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168Direct Cellularity Estimation on Breast Cancer Histopathology Images Using Transfer Learning
Ziang Pei,Shuangliang Cao,Lijun Lu,Wufan Chen
Computational and Mathematical Methods in Medicine.2019;2019(11)1
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169Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer
Jon Whitney,German Corredor,Andrew Janowczyk,Shridar Ganesan,Scott Doyle,John Tomaszewski,Michael Feldman,Hannah Gilmore,Anant Madabhushi
BMC Cancer.2018;18(1)1
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170Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer
Oscar Jimenez-del-Toro,Sebastian Otálora,Mats Andersson,Kristian Eurén,Martin Hedlund,Mikael Rousson,Henning Müller,Manfredo Atzori
BMC Cancer.2017;18(1)281
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171Predicting Infectious Disease Using Deep Learning and Big Data
Sangwon Chae,Sungjun Kwon,Donghyun Lee
International Journal of Environmental Research and Public Health.2018;15(8)1596
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172Predicting Infectious Disease Using Deep Learning and Big Data
Matthias Kohl,Christoph Walz,Florian Ludwig,Stefan Braunewell,Maximilian Baust
International Journal of Environmental Research and Public Health.2018;10882(8)903
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173Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
Zhichao Liu,Erika P. Portero,Yiren Jian,Yunjie Zhao,Rosemary M. Onjiko,Chen Zeng,Peter Nemes
Analytical Chemistry.2019;91(9)5768
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174Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
Azam Hamidinekoo,Reyer Zwiggelaar
Analytical Chemistry.2017;10553(9)213
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175Artificial 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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176Medical Image Analysis using Convolutional Neural Networks: A Review
Syed Muhammad Anwar,Muhammad Majid,Adnan Qayyum,Muhammad Awais,Majdi Alnowami,Muhammad Khurram Khan
Journal of Medical Systems.2018;42(11)500
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177Medical Image Analysis using Convolutional Neural Networks: A Review
Rucha Tambe,Sarang Mahajan,Urmil Shah,Mohit Agrawal,Bhushan Garware
Journal of Medical Systems.2019;42(11)143
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178Medical Image Analysis using Convolutional Neural Networks: A Review
Hui Qu,Gregory Riedlinger,Pengxiang Wu,Qiaoying Huang,Jingru Yi,Subhajyoti De,Dimitris Metaxas
Journal of Medical Systems.2019;42(11)900
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179A 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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180Predicting 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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181Multi-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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182Discovering 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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183Training 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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184Fluorescence-based quantification of nucleocytoplasmic transport
Joshua B. Kelley,Bryce M. Paschal
Methods.2019;157(2)106
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185Bringing 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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186Bringing 3D tumor models to the clinic - predictive value for personalized medicine
Yoshinori Kabeya,Toshiya Iwamori,Sho Yonezawa,Yusuke Takeuchi,Hiroki Nakano,Yuhe Nagisa,Mariko Okubo,Michio Inoue,Reitaro Tokumasu,Issei Ozawa,Atsushi Takano,Ichizo Nishino
Biotechnology Journal.2019;12(2)1850
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187Bringing 3D tumor models to the clinic - predictive value for personalized medicine
Ziqian Luo,Xiangrui Zeng,Zhipeng Bao,Min Xu
Biotechnology Journal.2019;12(2)1
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