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。Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
Hyuna Sung et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2021)
Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning
Yu-Heng Lai et al.
SCIENTIFIC REPORTS (2020)
Late fusion of multimodal deep neural networks for weeds classification
Vo Hoang Trong et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)
Weakly-supervised learning for lung carcinoma classification using deep learning
Fahdi Kanavati et al.
SCIENTIFIC REPORTS (2020)
Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets
Juan M. Galvez et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Shih-Cheng Huang et al.
NPJ DIGITAL MEDICINE (2020)
Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method
Baoshan Ma et al.
JOURNAL OF CANCER (2020)
Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level
Daniel Castillo et al.
PLOS ONE (2019)
Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT
Yutong Xie et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
Diego Ardila et al.
NATURE MEDICINE (2019)
Deep learning with multimodal representation for pancancer prognosis prediction
Anika Cheerla et al.
BIOINFORMATICS (2019)
MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework
Garam Lee et al.
FRONTIERS IN GENETICS (2019)
Detection of Lung Cancer Lymph Node Metastases from Whole-Slide Histopathologic Images Using a Two-Step Deep Learning Approach
Hoa Hoang Ngoc Pham et al.
AMERICAN JOURNAL OF PATHOLOGY (2019)
MLW-gcForest: a multi-weighted gcForest model towards the staging of lung adenocarcinoma based on multi-modal genetic data
Yunyun Dong et al.
BMC BIOINFORMATICS (2019)
Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients
Johannes Smolander et al.
BMC CANCER (2019)
Open Targets Platform: new developments and updates two years on
Denise Carvalho-Silva et al.
NUCLEIC ACIDS RESEARCH (2019)
Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice
Nikola Simidjievski et al.
FRONTIERS IN GENETICS (2019)
Feature Selection and Assessment of Lung Cancer Sub-types by Applying Predictive Models
Sara Gonzalez et al.
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2019, PT II (2019)
Precision medicine needs pioneering clinical bioinformaticians
Gonzalo Gomez-Lopez et al.
BRIEFINGS IN BIOINFORMATICS (2019)
Integrative network analysis identifies novel drivers of pathogenesis and progression in newly diagnosed multiple myeloma
A. Lagana et al.
LEUKEMIA (2018)
Identification of an early diagnostic biomarker of lung adenocarcinoma based on co-expression similarity and construction of a diagnostic model
Zhirui Fan et al.
JOURNAL OF TRANSLATIONAL MEDICINE (2018)
Construction of a specific SVM classifier and identification of molecular markers for lung adenocarcinoma based on IncRNA-miRNAmRNA network
Jingming Zhao et al.
ONCOTARGETS AND THERAPY (2018)
Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images
Pegah Khosravi et al.
EBIOMEDICINE (2018)
Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning
Nicolas Coudray et al.
NATURE MEDICINE (2018)
Systemic Therapy for Stage IV Non-Small-Cell Lung Cancer: American Society of Clinical Oncology Clinical Practice Guideline Update
Nasser Hanna et al.
JOURNAL OF CLINICAL ONCOLOGY (2017)
Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling
Daniel Castillo et al.
BMC BIOINFORMATICS (2017)
A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping
Qing Wen et al.
BMC BIOINFORMATICS (2016)
Toward a Shared Vision for Cancer Genomic Data
Robert L. Grossman et al.
NEW ENGLAND JOURNAL OF MEDICINE (2016)
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
Kun-Hsing Yu et al.
NATURE COMMUNICATIONS (2016)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
limma powers differential expression analyses for RNA-sequencing and microarray studies
Matthew E. Ritchie et al.
NUCLEIC ACIDS RESEARCH (2015)
Multimodal fusion framework: A multiresolution approach for emotion classification and recognition from physiological signals
Gyanendra K. Verma et al.
NEUROIMAGE (2014)
The Cancer Genome Atlas Pan-Cancer analysis project
John N. Weinstein et al.
NATURE GENETICS (2013)
Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography
Adrien Depeursinge et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2010)
Comparison of aspects of smoking among the four histological types of lung cancer
S. A. Kenfield et al.
TOBACCO CONTROL (2008)
Stability of feature selection algorithms: a study on high-dimensional spaces
Alexandros Kalousis et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2007)
Resampling methods for parameter-free and robust feature selection with mutual information
D. Francois et al.
NEUROCOMPUTING (2007)
Lung cancer in never smokers: A review
Janakiraman Subramanian et al.
JOURNAL OF CLINICAL ONCOLOGY (2007)
What is a support vector machine?
William S. Noble
NATURE BIOTECHNOLOGY (2006)
Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy
HC Peng et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2005)
Asymptotic behaviors of support vector machines with Gaussian kernel
SS Keerthi et al.
NEURAL COMPUTATION (2003)