| 1 |
Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma |
|
|
| Siteng Chen, Ning Zhang, Liren Jiang, Feng Gao, Jialiang Shao, Tao Wang, Encheng Zhang, Hong Yu, Xiang Wang, Junhua Zheng |
|
| International Journal of Cancer. 2021; 148(3): 780 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 2 |
Development of a Histopathology Informatics Pipeline for Classification and Prediction of Clinical Outcomes in Subtypes of Renal Cell Carcinoma |
|
|
| Eliana Marostica, Rebecca Barber, Thomas Denize, Isaac S. Kohane, Sabina Signoretti, Jeffrey A. Golden, Kun-Hsing Yu |
|
| Clinical Cancer Research. 2021; 27(10): 2868 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 3 |
Deep Convolutional Neural Network-Based Lymph Node Metastasis Prediction for Colon Cancer Using Histopathological Images |
|
|
| Min Seob Kwak, Hun Hee Lee, Jae Min Yang, Jae Myung Cha, Jung Won Jeon, Jin Young Yoon, Ha Il Kim |
|
| Frontiers in Oncology. 2021; 10 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 4 |
Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma |
|
|
| Hui Li, Linyan Chen, Hao Zeng, Qimeng Liao, Jianrui Ji, Xuelei Ma |
|
| Frontiers in Oncology. 2021; 11 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 5 |
DEEP LEARNING SURVIVAL PREDICTION FOR LUNG CANCER PATIENTS |
|
|
| Caiyun Huang, Changhua Yin |
|
| Biomedical Engineering: Applications, Basis and Communications. 2021; 33(04): 2150031 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 6 |
Standardized Method for Defining a 1-mm2 Region of Interest for Calculation of Mitotic Rate on Melanoma Whole Slide Images |
|
|
| Minhua Wang, Phyu P. Aung, Victor G. Prieto |
|
| Archives of Pathology & Laboratory Medicine. 2021; 145(10): 1255 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 7 |
Clinical Decision Support for Ovarian Carcinoma Subtype Classification: A Pilot Observer Study With Pathology Trainees |
|
|
| Marios A. Gavrielides, Meghan Miller, Ian S. Hagemann, Heba Abdelal, Zahra Alipour, Jie-Fu Chen, Behzad Salari, Lulu Sun, Huifang Zhou, Jeffrey D Seidman |
|
| Archives of Pathology & Laboratory Medicine. 2020; 144(7): 869 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 8 |
Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches |
|
|
| Peng-Nien Yin, Kishan KC, Shishi Wei, Qi Yu, Rui Li, Anne R. Haake, Hiroshi Miyamoto, Feng Cui |
|
| BMC Medical Informatics and Decision Making. 2020; 20(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 9 |
Classification and Prognosis Prediction from Histopathological Images of Hepatocellular Carcinoma by a Fully Automated Pipeline Based on Machine Learning |
|
|
| Haotian Liao, Tianyuan Xiong, Jiajie Peng, Lin Xu, Mingheng Liao, Zhen Zhang, Zhenru Wu, Kefei Yuan, Yong Zeng |
|
| Annals of Surgical Oncology. 2020; 27(7): 2359 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 10 |
Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
|
|
| Mohamed Amgad, Elisabeth Specht Stovgaard, Eva Balslev, Jeppe Thagaard, Weijie Chen, Sarah Dudgeon, Ashish Sharma, Jennifer K. Kerner, Carsten Denkert, Yinyin Yuan, Khalid AbdulJabbar, Stephan Wienert, Peter Savas, Leonie Voorwerk, Andrew H. Beck, Anant Madabhushi, Johan Hartman, Manu M. Sebastian, Hugo M. Horlings, Jan Hudecek, Francesco Ciompi, David A. Moore, Rajendra Singh, Elvire Roblin, Marcelo Luiz Balancin, Marie-Christine Mathieu, Jochen K. Lennerz, Pawan Kirtani, I-Chun Chen, Jeremy P. Braybrooke, Giancarlo Pruneri, Sandra Demaria, Sylvia Adams, Stuart J. Schnitt, Sunil R. Lakhani, Federico Rojo, Laura Comerma, Sunil S. Badve, Mehrnoush Khojasteh, W. Fraser Symmans, Christos Sotiriou, Paula Gonzalez-Ericsson, Katherine L. Pogue-Geile, Rim S. Kim, David L. Rimm, Giuseppe Viale, Stephen M. Hewitt, John M. S. Bartlett, Frédérique Penault-Llorca, Shom Goel, Huang-Chun Lien, Sibylle Loibl, Zuzana Kos, Sherene Loi, Matthew G. Hanna, Stefan Michiels, Marleen Kok, Torsten O. Nielsen, |
|
| npj Breast Cancer. 2020; 6(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 11 |
Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks |
|
|
| Kun-Hsing Yu, Feiran Wang, Gerald J Berry, Christopher Ré, Russ B Altman, Michael Snyder, Isaac S Kohane |
|
| Journal of the American Medical Informatics Association. 2020; 27(5): 757 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 12 |
Derivation of a nuclear heterogeneity image index to grade DCIS |
|
|
| Mary-Kate Hayward, J. Louise Jones, Allison Hall, Lorraine King, Alastair J. Ironside, Andrew C. Nelson, E. Shelley Hwang, Valerie M. Weaver |
|
| Computational and Structural Biotechnology Journal. 2020; 18: 4063 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 13 |
Automated Osteosclerosis Grading of Clinical Biopsies Using Infrared Spectroscopic Imaging |
|
|
| Rupali Mankar, Carlos E. Bueso-Ramos, C. Cameron Yin, Juliana Elisa Hidalgo-Lopez, Sebastian Berisha, Mustafa Kansiz, David Mayerich |
|
| Analytical Chemistry. 2020; 92(1): 749 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 14 |
A structured latent model for ovarian carcinoma subtyping from histopathology slides |
|
|
| Aïcha BenTaieb,Hector Li-Chang,David Huntsman,Ghassan Hamarneh |
|
| Medical Image Analysis. 2017; 39: 194 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 15 |
Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis |
|
|
| Jun Cheng, Jie Zhang, Yatong Han, Xusheng Wang, Xiufen Ye, Yuebo Meng, Anil Parwani, Zhi Han, Qianjin Feng, Kun Huang |
|
| Cancer Research. 2017; 77(21): e91 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 16 |
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features |
|
|
| Kun-Hsing Yu,Ce Zhang,Gerald J. Berry,Russ B. Altman,Christopher Ré,Daniel L. Rubin,Michael Snyder |
|
| Nature Communications. 2016; 7: 12474 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 17 |
A survey on automated cancer diagnosis from histopathology images |
|
|
| J. Angel Arul Jothi,V. Mary Anita Rajam |
|
| Artificial Intelligence Review. 2016; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 18 |
A robust nonlinear tissue-component discrimination method for computational pathology |
|
|
| Jacob S Sarnecki,Kathleen H Burns,Laura D Wood,Kevin M Waters,Ralph H Hruban,Denis Wirtz,Pei-Hsun Wu |
|
| Laboratory Investigation. 2016; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 19 |
Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays |
|
|
| Sahirzeeshan Ali,Robert Veltri,Jonathan I. Epstein,Christhunesa Christudass,Anant Madabhushi |
|
| Computerized Medical Imaging and Graphics. 2014; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 20 |
Validating Whole Slide Digital Morphometric Analysis as a Microscopy Tool |
|
|
| Robert B. Diller,Robert S. Kellar |
|
| Microscopy and Microanalysis. 2014; : 1 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 21 |
Wide-field computational imaging of pathology slides using lens-free on-chip microscopy |
|
|
| A. Greenbaum,Y. Zhang,A. Feizi,P.-L. Chung,W. Luo,S. R. Kandukuri,A. Ozcan |
|
| Science Translational Medicine. 2014; 6(267): 267ra175 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 22 |
Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer |
|
|
| Scott Doyle,Michael D Feldman,Natalie Shih,John Tomaszewski,Anant Madabhushi |
|
| BMC Bioinformatics. 2012; 13(1): 282 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 23 |
Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer |
|
|
| Mitko Veta,Robert Kornegoor,André Huisman,Anoek H J Verschuur-Maes,Max A Viergever,Josien P W Pluim,Paul J van Diest |
|
| Modern Pathology. 2012; 25(12): 1559 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 24 |
Review and Cross-Validation of Gene Expression Signatures and Melanoma Prognosis |
|
|
| Sarah-Jane Schramm,Anna E Campain,Richard A Scolyer,Yee Hwa Yang,Graham J Mann |
|
| Journal of Investigative Dermatology. 2012; 132(2): 274 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
