相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis
Mahmut Yurt et al.
MEDICAL IMAGE ANALYSIS (2021)
Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes
Doris Leithner et al.
MOLECULAR IMAGING AND BIOLOGY (2020)
Evaluating missing value imputation methods for food composition databases
Gordana Ispirova et al.
FOOD AND CHEMICAL TOXICOLOGY (2020)
Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion
Chengqian Lu et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)
Handling incomplete heterogeneous data using VAEs
Alfredo Nazabal et al.
PATTERN RECOGNITION (2020)
Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation
Olivia Choudhury et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2019)
Integration of dynamic contrast-enhanced magnetic resonance imaging and T2-weighted imaging radiomic features by a canonical correlation analysis-based feature fusion method to predict histological grade in ductal breast carcinoma
Ming Fan et al.
PHYSICS IN MEDICINE AND BIOLOGY (2019)
Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks
Salman U. H. Dar et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)
DeepMF: deciphering the latent patterns in omics profiles with a deep learning method
Lingxi Chen et al.
BMC BIOINFORMATICS (2019)
Radiomic analysis of imaging heterogeneity in tumours and the surrounding parenchyma based on unsupervised decomposition of DCE-MRI for predicting molecular subtypes of breast cancer
Ming Fan et al.
EUROPEAN RADIOLOGY (2019)
Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics
Ming Fan et al.
IEEE Journal of Biomedical and Health Informatics (2019)
DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 status of estrogen receptor-positive breast cancers
Ming Fan et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2018)
Matrix completion by deep matrix factorization
Jicong Fan et al.
NEURAL NETWORKS (2018)
Dynamic Contrast-Enhanced and Diffusion-Weighted MRI of Estrogen Receptor-Positive Invasive Breast Cancers: Associations Between Quantitative MR Parameters and Ki-67 Proliferation Status
Jong Ki Shin et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2017)
GeneImp: Fast Imputation to Large Reference Panels Using Genotype Likelihoods from Ultralow Coverage Sequencing
Athina Spiliopoulou et al.
GENETICS (2017)
GeneImp: Fast Imputation to Large Reference Panels Using Genotype Likelihoods from Ultralow Coverage Sequencing
Athina Spiliopoulou et al.
GENETICS (2017)
Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer
Ming Fan et al.
PLOS ONE (2017)
Computational Radiomics System to Decode the Radiographic Phenotype
Joost J. M. van Griethuysen et al.
CANCER RESEARCH (2017)
Neural Collaborative Filtering
Xiangnan He et al.
PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'17) (2017)
Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set
Hui Li et al.
NPJ BREAST CANCER (2016)
An Efficient Non-Negative Matrix-Factorization-Based Approach to Collaborative Filtering for Recommender Systems
Xin Luo et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2014)
Ki-67 as a Predictor of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients
Kwan Il Kim et al.
JOURNAL OF BREAST CANCER (2014)
Computer-Aided Diagnosis of Breast DCE-MRI Images Using Bilateral Asymmetry of Contrast Enhancement Between Two Breasts
Qian Yang et al.
JOURNAL OF DIGITAL IMAGING (2014)
Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients
M. J. Engstrom et al.
BREAST CANCER RESEARCH AND TREATMENT (2013)
Genotype imputation via matrix completion
Eric C. Chi et al.
GENOME RESEARCH (2013)
Correlation between Ki67 and Breast Cancer Prognosis
Konstantinos Kontzoglou et al.
ONCOLOGY (2013)
Fuzzy min-max neural networks for categorical data: application to missing data imputation
Pilar Rey-del-Castillo et al.
NEURAL COMPUTING & APPLICATIONS (2012)
Missing value imputation for gene expression data: computational techniques to recover missing data from available information
Alan Wee-Chung Liew et al.
BRIEFINGS IN BIOINFORMATICS (2011)
The Changing Role of Pathology in Breast Cancer Diagnosis and Treatment
Anthony S. -Y. Leong et al.
PATHOBIOLOGY (2011)
Dealing with missing values in large-scale studies: microarray data imputation and beyond
Tero Aittokallio
BRIEFINGS IN BIOINFORMATICS (2010)
Immunohistochemical Surrogate Markers of Breast Cancer Molecular Classes Predicts Response to Neoadjuvant Chemotherapy A Single Institutional Experience With 359 Cases
Rohit Bhargava et al.
CANCER (2010)
Breast Cancer Subtypes and the Risk of Local and Regional Relapse
K. David Voduc et al.
JOURNAL OF CLINICAL ONCOLOGY (2010)
Breast Cancer Molecular Subtypes in Patients With Locally Advanced Disease: Impact on Prognosis, Patterns of Recurrence, and Response to Therapy
Kathryn E. Huber et al.
SEMINARS IN RADIATION ONCOLOGY (2009)
Missing value estimation for DNA microarray gene expression data: local least squares imputation (vol 21, pg 187, 2005)
H Kim et al.
BIOINFORMATICS (2006)
A hybrid neural network system for pattern classification tasks with missing features
CP Lim et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2005)