Alle Papers – KI in der Krebserkennung
172.746 Papers insgesamt · Seite 92 von 400
Deep learning for identifying radiogenomic associations in breast cancer
Boosted neural network ensemble classification for lung cancer disease diagnosis
Completely Automated Segmentation Approach for Breast Ultrasound Images Using Multiple-Domain Features
An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm
Multi-Class Skin Lesion Detection and Classification via Teledermatology
Optimizing Survival Analysis of XGBoost for Ties to Predict Disease Progression of Breast Cancer
Basic Physics and Doubts about Relationship between Mammographically Determined Tissue Density and Breast Cancer Risk
Symmetry of projection in the quantitative analysis of mammographic images
Supervised machine learning tools: a tutorial for clinicians
Inter- and intraradiologist variability in the BI-RADS assessment and breast density categories for screening mammograms
A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs
Harnessing non-destructive 3D pathology
Neural network classifier optimization using Differential Evolution with Global Information and Back Propagation algorithm for clinical datasets
Breast tomosynthesis in clinical practice: initial results
Decision Support Systems in Oncology
An expert system for selecting wart treatment method
Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms
Foundation model for cancer imaging biomarkers
Using DUCK-Net for polyp image segmentation
An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images
Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network
Survey on Machine Learning and Deep Learning Applications in Breast Cancer Diagnosis
Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions
Graph CNN for Survival Analysis on Whole Slide Pathological Images
Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis