Research graph
References from Deep Learning of radiology-genomics integration for computational oncology: A mini review. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1146/annurev-genet-112414-054842
10.1146/annurev-genet-112414-054842 · External reference
10.1016/j.cell.2023.07.014
10.1016/j.cell.2023.07.014 · External reference
Artificial intelligence for multimodal data integration in oncology
10.1016/j.ccell.2022.09.012 · 2022 · External reference
10.1038/s41568-021-00408-3
10.1038/s41568-021-00408-3 · External reference
10.1038/nbt.4233
10.1038/nbt.4233 · External reference
10.1038/s42256-023-00633-5
10.1038/s42256-023-00633-5 · External reference
An integrated tcga pan-cancer clinical data resource to drive high-quality survival outcome analytics
10.1016/j.cell.2018.02.052 · 2018 · External reference
The international cancer genome consortium data portal
10.1038/s41587-019-0055-9 · 2019 · External reference
Mining whole-lung information by artificial intelligence for predicting EGFR genotype and targeted therapy response in lung cancer: a multicohort study
10.1016/s2589-7500(22)00024-3 · 2022 · External reference
10.1016/j.cllc.2016.02.001
10.1016/j.cllc.2016.02.001 · External reference
Predictive radiogenomics modeling of EGFR mutation status in lung cancer
10.1038/srep41674 · 2017 · External reference
Radiogenomic models using machine learning techniques to predict EGFR mutations in non-small cell lung cancer
10.1177/0846537119899526 · 2021 · External reference
Radiogenomics: what it is and why it is important
10.1016/j.jacr.2015.04.019 · 2015 · External reference
10.1038/s41591-022-01981-2
10.1038/s41591-022-01981-2 · External reference
Rise of deep learning clinical applications and challenges in omics data: a systematic review
10.3390/diagnostics13040664 · 2023 · External reference
10.1007/s00432-022-04161-4
10.1007/s00432-022-04161-4 · External reference
Radiogenomics: bridging imaging and genomics
10.1007/s00261-019-02028-w · 2019 · External reference
XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data
10.1093/bib/bbab315 · 2021 · External reference
Non-invasive prediction of microsatellite instability in colorectal cancer by a genetic algorithm-enhanced artificial neural network-based CT radiomics signature
10.1007/s00330-022-08954-6 · 2023 · External reference
Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study
2023 · External reference
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
10.1186/s12874-018-0482-1 · 2018 · External reference
Contrast-enhanced CT texture analysis in colon cancer: correlation with genetic markers
10.3390/tomography8050184 · 2022 · External reference
Unresolved reference
2022 · External reference
Transformers in vision: a survey
10.1145/3505244 · 2022 · External reference
Visual transformers and convolutional neural networks for disease classification on radiographs: a comparison of performance, sample efficiency, and hidden stratification
2022 · External reference
Attention-based Saliency Maps Improve Interpretability of Pneumothorax Classification
2022 · External reference
A comprehensive survey on graph neural networks
10.1109/tnnls.2020.2978386 · 2020 · External reference
Graph neural networks: a review of methods and applications
10.1016/j.aiopen.2021.01.001 · 2020 · External reference
Multimodal learning with graphs
10.1038/s42256-023-00624-6 · 2023 · External reference
Predicting transcriptional outcomes of novel multigene perturbations with GEARS
2023 · External reference
MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification
10.1038/s41467-021-23774-w · 2021 · External reference
10.1038/s41592-021-01255-8
10.1038/s41592-021-01255-8 · External reference
Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer
10.1186/s13073-021-00845-7 · 2021 · External reference
PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data
2018 · External reference
Investigating the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning model
10.1186/s12859-020-03850-6 · 2021 · External reference
Biologically informed deep neural network for prostate cancer discovery
10.1038/s41586-021-03922-4 · 2021 · External reference
PAUSE: principled feature attribution for unsupervised gene expression analysis
10.1186/s13059-023-02901-4 · 2023 · External reference
A deep learning approach to diagnostic classification of prostate cancer using pathology–radiology fusion
10.1002/jmri.27599 · 2021 · External reference
Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas
10.1186/s41199-020-00053-7 · 2020 · External reference
10.1016/j.acra.2009.02.014
10.1016/j.acra.2009.02.014 · External reference
Adjusted CT image-based radiomic features combined with immune genomic expression achieve accurate prognostic classification and identification of therapeutic targets in stage iii colorectal cancer
10.3390/cancers14081895 · 2022 · External reference
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)
2021 · External reference
10.1016/j.radonc.2021.12.031
10.1016/j.radonc.2021.12.031 · External reference
Multimodal deep learning for prognosis prediction in renal cancer
10.3389/fonc.2021.788740 · 2021 · External reference
Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma
10.1016/j.radonc.2020.09.014 · 2021 · External reference
Cross-modal autoencoder framework learns holistic representations of cardiovascular state
10.1038/s41467-023-38125-0 · 2023 · External reference
Explainable multi-task learning for multi-modality biological data analysis
10.1038/s41467-023-37477-x · 2023 · External reference
10.1016/j.ccell.2022.07.004
10.1016/j.ccell.2022.07.004 · External reference
Benefits and harms of CT screening for lung cancer: a systematic review
10.1001/jama.2012.5521 · 2012 · External reference
Deep learning for lung cancer nodules detection and classification in CT scans
10.3390/ai1010003 · 2020 · External reference
Deep learning for lung Cancer detection and classification
10.1007/s11042-019-08394-3 · 2020 · External reference
Detection of clinically significant prostate cancer using magnetic resonance imaging–ultrasound fusion targeted biopsy: a systematic review
10.1016/j.eururo.2014.10.026 · 2015 · External reference
Unresolved reference
2016 · External reference
Glioma segmentation with a unified algorithm in multimodal MRI images
2018 · External reference
Pilot study demonstrating potential association between breast cancer image‐based risk phenotypes and genomic biomarkers
2014 · External reference
CT radiogenomic characterization of EGFR, K-RAS, and ALK mutations in non-small cell lung cancer
10.1007/s00330-015-3814-0 · 2016 · External reference
Correlation between genomic index lesions and mpMRI and 68Ga-PSMA-PET/CT imaging features in primary prostate cancer
10.1038/s41598-018-35058-3 · 2018 · External reference
Genomic risk predicts molecular imaging-detected metastatic nodal disease in prostate cancer
10.1016/j.euo.2018.11.002 · 2019 · External reference
DNA damage and gene expression changes in patients exposed to low-dose X-radiation during neuro-interventional radiology procedures
10.1016/j.mrgentox.2019.05.011 · 2019 · External reference
Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects
10.3390/ijms24054615 · 2023 · External reference
Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer
2021 · External reference
Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer
10.3748/wjg.v26.i19.2388 · 2020 · External reference
10.1007/978-3-030-89847-2_3
10.1007/978-3-030-89847-2_3 · External reference
CT-based radiogenomic analysis dissects intratumor heterogeneity and predicts prognosis of colorectal cancer: a multi-institutional retrospective study
10.1186/s12967-022-03788-8 · 2022 · External reference
Diagnosis of glioblastoma multiforme progression via interpretable structure-constrained graph neural networks
10.1109/tmi.2022.3202037 · 2023 · External reference
Multi-size deep learning based preoperative computed tomography signature for prognosis prediction of colorectal cancer
2022 · External reference
10.1109/iccv.2017.74
10.1109/iccv.2017.74 · External reference
Unresolved reference
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Medimlp: using grad-cam to extract crucial variables for lung cancer postoperative complication prediction
10.1109/jbhi.2019.2949601 · 2019 · External reference
Unresolved reference
2021 · External reference
Lung Cancer Classification Using Squeeze and Excitation Convolutional Neural Networks with Grad Cam++ Class Activation Function
2021 · External reference
A unified approach to interpreting model predictions
2017 · External reference
Unresolved reference
2019 · External reference
Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment
2023 · External reference
VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics
10.1038/s41467-021-26017-0 · 2021 · External reference
Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
10.1038/s41467-021-25534-2 · 2021 · External reference
Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review
10.1016/j.ejca.2021.10.007 · 2022 · External reference
10.1145/3219819.3219963
10.1145/3219819.3219963 · External reference
Unresolved reference
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Unresolved reference
2021 · External reference
10.1007/978-3-031-25072-9_42
10.1007/978-3-031-25072-9_42 · External reference
10.18653/v1/p19-1656
10.18653/v1/p19-1656 · 2019 · External reference
Alignment in multimodal interaction: An integrative framework
10.1111/cogs.12911 · 2020 · External reference
An approach to multimodal biomedical image registration utilizing particle swarm optimization
10.1109/tevc.2004.826068 · 2004 · External reference
Correlated multimodal imaging in life sciences: expanding the biomedical horizon
10.3389/fphy.2020.00047 · 2020 · External reference
Multimodal image alignment via linear mapping between feature modalities
10.1155/2017/8625951 · 2017 · External reference
A full migration BBO algorithm with enhanced population quality bounds for multimodal biomedical image registration
10.1016/j.asoc.2020.106335 · 2020 · External reference
Unresolved reference
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Unresolved reference
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Unresolved reference
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A foundation model for generalizable disease detection from retinal images
10.1038/s41586-023-06555-x · 2023 · External reference
10.1038/s41551-023-01049-7
10.1038/s41551-023-01049-7 · External reference
10.1038/s42256-022-00534-z
10.1038/s42256-022-00534-z · External reference
10.1038/s41586-023-05881-4
10.1038/s41586-023-05881-4 · External reference
10.1007/s40484-016-0061-6
10.1007/s40484-016-0061-6 · External reference
Development and clinical application of radiomics in lung cancer
10.1186/s13014-017-0885-x · 2017 · External reference
Detection of patient-level distances from single cell genomics and pathomics data with optimal transport (PILOT)
10.1038/s44320-023-00003-8 · 2024 · External reference
A novel pathomics signature for gastric cancer
10.1038/s41575-022-00719-2 · 2023 · External reference
10.1016/j.cell.2011.02.013
10.1016/j.cell.2011.02.013 · External reference
10.1016/j.csbj.2022.10.001 · Admitted local publication
Next-Generation Morphometry for pathomics-data mining in histopathology
10.1038/s41467-023-36173-0 · 2023 · External reference
Prognostic and predictive value of a pathomics signature in gastric cancer
10.1038/s41467-022-34703-w · 2022 · External reference
Predicting peritoneal recurrence in gastric cancer with serosal invasion using a pathomics nomogram
2023 · External reference
TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
2024 · External reference
10.1093/bioinformatics/btz318
10.1093/bioinformatics/btz318 · External reference
Artificial intelligence in musculoskeletal oncology imaging: a critical review of current applications
10.1016/j.diii.2022.10.004 · 2023 · External reference
Explainable artificial intelligence for omics data: a systematic mapping study
10.1093/bib/bbad453 · 2023 · External reference
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
10.1016/j.compbiomed.2019.05.002 · 2019 · External reference
Molecular subtyping of diffuse gliomas using magnetic resonance imaging: Comparison and correlation between radiomics and deep learning
10.1007/s00330-021-08237-6 · 2022 · External reference
Convolutional neural network using a breast MRI tumor dataset can predict oncotype Dx recurrence score
10.1002/jmri.26244 · 2019 · External reference
Predicting breast cancer molecular subtype with MRI dataset utilizing convolutional neural network algorithm
10.1007/s10278-019-00179-2 · 2019 · External reference
Prediction of breast cancer molecular subtypes on DCE-MRI using convolutional neural network with transfer learning between two centers
10.1007/s00330-020-07274-x · 2021 · External reference
Deep learning for lung cancer prognostication: a retrospective multi-cohort radiomics study
10.1371/journal.pmed.1002711 · 2018 · External reference
10.1148/radiol.14140789
10.1148/radiol.14140789 · External reference
Nomograms based on preoperative multiparametric magnetic resonance imaging for prediction of molecular subgrouping in medulloblastoma: results from a radiogenomics study of 111 patients
10.1093/neuonc/noy093 · 2019 · External reference
DADFN: dynamic adaptive deep fusion network based on imaging genomics for prediction recurrence of lung cancer
2023 · External reference
10.1007/978-3-031-16443-9_60
10.1007/978-3-031-16443-9_60 · External reference
Integrating radiomics with genomics for non-small cell lung cancer survival analysis
2022 · External reference
