Alle Papers – KI in der Krebserkennung
168.310 Papers insgesamt · Seite 13 von 400
Object-Based Image Analysis
Role of Sonography in the Diagnosis of Axillary Lymph Node Metastases in Breast Cancer: A Systematic Review
Big Self-Supervised Models Advance Medical Image Classification
Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction
The Clinician and Dataset Shift in Artificial Intelligence
Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment
A support vector machine approach for detection of microcalcifications
How Machine Learning Will Transform Biomedicine
Multi-scale Convolutional Neural Networks for Lung Nodule Classification
Machine and deep learning methods for radiomics
Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task
OpenSlide: A vendor-neutral software foundation for digital pathology
Self-supervised learning in medicine and healthcare
A review of the application of deep learning in medical image classification and segmentation
Harnessing multimodal data integration to advance precision oncology
Computer-aided detection and classification of microcalcifications in mammograms: a survey
DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning
Potential Contribution of Computer-aided Detection to the Sensitivity of Screening Mammography
NiftyNet: a deep-learning platform for medical imaging
Machine learning for medical imaging: methodological failures and recommendations for the future
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
Within the Lack of Chest COVID-19 X-ray Dataset: A Novel Detection Model Based on GAN and Deep Transfer Learning
Attention Residual Learning for Skin Lesion Classification
Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features