Research graph
References from Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis. Local targets link to admitted publications; unresolved targets remain external evidence.
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2018 · External reference
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2020 · External reference
Deep learning applied for histological diagnosis of breast cancer
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Deep learning and optimization algorithms for automatic breast cancer detection
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Deep learning based breast cancer detection and classification using fuzzy merging techniques
10.1007/s00138-020-01122-0 · 2020 · External reference
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10.3390/s20164373 · External reference
Classification of breast cancer histology images using multi-size and discriminative patches based on deep learning
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Breast cancer detection using extreme learning machine based on feature fusion with CNN deep features
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Liver cancer detection using hybridized fully convolutional neural network based on deep learning framework
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Automatic skin cancer detection in dermoscopy images based on ensemble lightweight deep learning network
10.1109/access.2020.2997710 · 2020 · External reference
A novel bio-inspired deep learning approach for liver cancer diagnosis
10.3390/info11020080 · 2020 · External reference
Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques
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Intelligent skin cancer diagnosis using improved particle swarm optimization and deep learning models
10.1016/j.asoc.2019.105725 · 2019 · External reference
Transition zone prostate cancer: logistic regression and machine-learning models of quantitative ADC, shape and texture features are highly accurate for diagnosis
10.1002/jmri.26674 · 2019 · External reference
Early lung cancer diagnostic biomarker discovery by machine learning methods
10.1016/j.tranon.2020.100907 · 2021 · External reference
CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features
10.1186/s12920-018-0436-9 · 2018 · External reference
Tree-based machine learning algorithms identified minimal set of miRNA biomarkers for breast cancer diagnosis and molecular subtyping
10.1016/j.gene.2018.07.057 · 2018 · External reference
10.1007/s00345-020-03392-9
10.1007/s00345-020-03392-9 · External reference
Early colorectal cancer detected by machine learning model using gender, age, and complete blood count data
10.1007/s10620-017-4722-8 · 2017 · External reference
Development of a machine learning-based multimode diagnosis system for lung cancer
10.18632/aging.103249 · 2020 · External reference
Application of machine learning in the diagnosis of gastric cancer based on noninvasive characteristics
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10.1016/j.ygeno.2020.06.035
10.1016/j.ygeno.2020.06.035 · External reference
A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method
2020 · External reference
Lung cancer histology classification from CT images based on radiomics and deep learning models
10.1007/s11517-020-02302-w · 2021 · External reference
Deep learning-based ovarian cancer subtypes identification using multi-omics data
2020 · External reference
10.1016/j.bspc.2020.101869
10.1016/j.bspc.2020.101869 · External reference
Optimal deep learning model for classification of lung cancer on CT images
10.1016/j.future.2018.10.009 · 2019 · External reference
Deep learning-based classification of liver cancer histopathology images using only global labels
10.1109/jbhi.2019.2949837 · 2019 · External reference
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Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA
2019 · External reference
Impact of machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy and survival outcomes in breast cancer patients
10.1097/rli.0000000000000518 · 2019 · External reference
Prediction of lung cancer patient survival via supervised machine learning classification techniques
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10.1016/j.ijmedinf.2020.104195
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10.1039/c9mo00198k · 2020 · External reference
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10.1101/557470 · External reference
Machine learning-based prediction of breast cancer growth rate in vivo
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Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening
10.1088/1361-6560/aaafab · 2018 · External reference
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Development and validation of a deep learning algorithm for Gleason grading of prostate cancer from biopsy specimens
10.1001/jamaoncol.2020.2485 · 2020 · External reference
Deep Learning-Based Gleason grading of prostate cancer from histopathology Images—Role of multiscale decision aggregation and data augmentation
10.1109/jbhi.2019.2944643 · 2019 · External reference
A deep learning approach to skin cancer detection in dermoscopy images
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Development and validation of a deep learning model for non–small cell lung cancer survival
10.1001/jamanetworkopen.2020.5842 · 2020 · External reference
Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis
2020 · External reference
Machine learning models for predicting post-cystectomy recurrence and survival in bladder cancer patients
10.1371/journal.pone.0210976 · 2019 · External reference
Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning
2020 · External reference
A survey on the explainability of supervised machine learning
10.1613/jair.1.12228 · 2021 · External reference
A historical perspective of explainable artificial intelligence
2021 · External reference
Automatic assessment of privacy policies under the GDPR
10.3390/app11041762 · 2021 · External reference
The deployment of artificial intelligence tools in the health sector: privacy concerns and regulatory answers within the GDPR
2021 · External reference
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10.3390/app11115088 · External reference
10.1016/j.csbj.2014.11.005
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10.1093/bib/bbz044
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