Research graph
References from Multimodal Deep Learning Fusion for Lung Cancer Subtype Differentiation from CT and PET Imaging. Local targets link to admitted publications; unresolved targets remain external evidence.
Multimodal biomedical AI
10.1038/s41591-022-01981-2 · External reference
Small-cell lung cancer
10.1038/s41572-020-00235-0 · External reference
10.1038/s41551-020-00682-w
10.1038/s41551-020-00682-w · 2021 · External reference
10.1038/s41586-023-05881-4
10.1038/s41586-023-05881-4 · 2023 · External reference
Research progress in computer-aided diagnosis systems for lung cancer
10.1038/s41746-025-02101-3 · External reference
10.1038/s41592-020-01008-z · 2021 · Admitted local publication
Unresolved reference
External reference
10.1186/s12880-024-01241-4
10.1186/s12880-024-01241-4 · 2024 · External reference
Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images
10.1038/s41598-022-24278-3 · External reference
Tackling class imbalance in computer vision: a contemporary review
10.1007/s10462-023-10557-6 · External reference
Unresolved reference
2018 · External reference
Integrating CT-based radiomics and deep learning for invasive prediction of ground-glass nodules in lung adenocarcinoma: a multicohort study
10.1186/s13244-025-02156-6 · External reference
Image fusion meets deep learning: A survey and perspective
10.1016/j.inffus.2021.06.008 · External reference
10.3389/fonc.2020.00418
10.3389/fonc.2020.00418 · External reference
Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules
10.1038/s41598-025-13447-9 · External reference
‘TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classication’
10.48550/arxiv.2106.00908 · 2021 · External reference
10.3390/cancers16061130
10.3390/cancers16061130 · 2024 · External reference
EMFusion: An unsupervised enhanced medical image fusion network
10.1016/j.inffus.2021.06.001 · External reference
Deep learning radiomics model based on PET/CT predicts PD-L1 expression in non-small cell lung cancer
10.1016/j.ejro.2024.100549 · External reference
10.1109/embc40787.2023.10340635
10.1109/embc40787.2023.10340635 · 2023 · External reference
Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer
10.1109/tmi.2019.2923601 · External reference
10.7150/thno.48027
10.7150/thno.48027 · 2021 · External reference
Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation
10.1038/s41598-024-61101-7 · External reference
Enhanced lung cancer subtype classification using attention-integrated DeepCNN and radiomic features from CT images: a focus on feature reproducibility
10.1007/s12672-025-02115-z · External reference
10.1007/978-3-030-87193-2_2
10.1007/978-3-030-87193-2_2 · 2021 · External reference
10.1038/s43018-022-00416-8
10.1038/s43018-022-00416-8 · 2022 · External reference
10.1016/j.clon.2023.08.003
10.1016/j.clon.2023.08.003 · 2023 · External reference
PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer
10.1038/s41467-023-42811-4 · External reference
10.1109/iccv48922.2021.00986
10.1109/iccv48922.2021.00986 · 2021 · External reference
Multi-level multi-modality (PET and CT) fusion radiomics: prognostic modeling for non-small cell lung carcinoma
10.1088/1361-6560/ac287d · External reference
Multimodal multitask deep learning for grading management system in non-small cell lung cancer
10.1038/s41467-026-74474-2 · External reference
10.1148/radiol.2020191145
10.1148/radiol.2020191145 · 2020 · External reference
Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights
10.1038/s41467-024-47512-0 · External reference
The future of digital health with federated learning
10.1038/s41746-020-00323-1 · External reference
10.1038/s41551-022-00936-9
10.1038/s41551-022-00936-9 · 2022 · External reference
10.1016/j.media.2022.102470
10.1016/j.media.2022.102470 · 2022 · External reference
