Latest Research in AI in cancer detection

Top Research Topics in AI in cancer detection

• AI in cancer detection — 20 papers
• Computer Vision and Pattern Recognition — 8 papers
• Digital Imaging for Blood Diseases — 4 papers
• Image and Video Processing — 2 papers
• Machine Learning — 2 papers
• Optical Imaging and Spectroscopy Techniques — 1 papers
• Radiomics and Machine Learning in Medical Imaging — 1 papers
• Medical Imaging Techniques and Applications — 1 papers
• Advanced Radiotherapy Techniques — 1 papers
• Medical Physics — 1 papers

Highest-Cited Papers

1. DeepBreastNet: Multi-Modal Deep Learning for Comprehensive Breast Cancer Diagnosis Across Heterogeneous Imaging Modalities
2. A segmentation-guided CNN–Vision transformer feature fusion framework for multi-class breast ultrasound image classification
3. Performance of Machine Learning Classification in Sonomammogram Images using BI-RADS
4. Enhanced breast cancer detection in mammograms using U-MDC based semantic segmentation and deep learning models for classification
5. A tri-branch multi-view contrastive learning framework integrated with physiological information for tumor classification in dynamic optical breast imaging data
6. A Lightweight CNN Integrated Compact Convolutional Transformer for Multi-Scale Feature Learning and reducing computational complexity for breast cancer mammography image detection and classification
7. Artificial intelligence-based PET/CT analysis in lymphoma: segmentation, differential diagnosis, and prognostic stratification
8. Explainable Machine Learning for Oncological Mass Classification: Benchmarking, Threshold Optimization and Robustness Analysis
9. Meta-attention fusion and adaptive optimization for explainable diagnosis of acute lymphoblastic leukemia in blood smears
10. Evaluating Contextual Bias in CNN Image Classification: Evidence from Agricultural Benchmark Datasets
11. ProtoCAM: Interpretable Few-Shot Mask-Guided Prototypical Learning for Breast Lesion Classification in Ultrasound Imaging
12. Grünwald–Letnikov Fractional Ensemble with α-Specific Power Weighting for Multi-Cancer Classification
13. Longitudinal Risk Prediction in Mammography with Privileged History Distillation
14. PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images
15. A hierarchical pipeline for preprocessing and classification of breast histopathology images into benign and malignant
16. Improved deep joint segmentation and deep hybrid architecture for breast cancer diagnosis with improved pattern extractors
17. Deep Learning in Multimodal Breast Cancer Imaging: From Image Reconstruction and Segmentation to Diagnosis and Treatment Response Prediction
18. Single-Scattered events Imaging in ToF-PET via Machine Learning-Based Classification
19. UPMA: unspecified pretraining and modular adaptation for context-aware target delineation in adaptive esophageal radiotherapy
20. Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial