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Lung Cancer Diagnosis

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Showing 26–50 of 63 papers

TitleStatusHype
Hybrid deep neural networks for all-cause Mortality Prediction from LDCT Images—0
Improving diagnosis and prognosis of lung cancer using vision transformers: A scoping review—0
Improving Lung Cancer Diagnosis and Survival Prediction with Deep Learning and CT Imaging—0
Interpretative Computer-aided Lung Cancer Diagnosis: from Radiology Analysis to Malignancy Evaluation—0
Investigating Quantum Feature Maps in Quantum Support Vector Machines for Lung Cancer Classification—0
Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining—0
LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model—0
Lung Cancer Detection Using Machine Learning Methods—0
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics—0
Lung Tumor Location and Identification with AlexNet and a Custom CNN—0
Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis—0
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan—0
Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer—0
3DFPN-HS^2: 3D Feature Pyramid Network Based High Sensitivity and Specificity Pulmonary Nodule Detection—0
Accurate and Robust Pulmonary Nodule Detection by 3D Feature Pyramid Network with Self-supervised Feature Learning—0
Advanced Lung Nodule Segmentation and Classification for Early Detection of Lung Cancer using SAM and Transfer Learning—0
An automated end-to-end deep learning-based framework for lung cancer diagnosis by detecting and classifying the lung nodules—0
Automated Report Generation for Lung Cytological Images Using a CNN Vision Classifier and Multiple-Transformer Text Decoders: Preliminary Study—0
Automatic Lung Cancer Prediction from Chest X-ray Images Using Deep Learning Approach—0
AutoRad-Lung: A Radiomic-Guided Prompting Autoregressive Vision-Language Model for Lung Nodule Malignancy Prediction—0
Characterization of Lung Nodule Malignancy using Hybrid Shape and Appearance Features—0
Semi-supervised multi-task learning for lung cancer diagnosis—0
Task-Specific Data Preparation for Deep Learning to Reconstruct Structures of Interest from Severely Truncated CBCT Data—0
Tool or Tutor? Experimental evidence from AI deployment in cancer diagnosis—0
TumorNet: Lung Nodule Characterization Using Multi-View Convolutional Neural Network with Gaussian Process—0
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