Alle Papers – KI in der Krebserkennung

Integrating spatial gene expression and breast tumour morphology via deep learning

A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

Breast cancer classification using deep belief networks

Deep Learning in Radiology

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

INet: Convolutional Networks for Biomedical Image Segmentation

Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy

Diagnostic Performance of Digital versus Film Mammography for Breast-Cancer Screening

Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning

Transparency and reproducibility in artificial intelligence

Texture features for classification of ultrasonic liver images

A scoping review of transfer learning research on medical image analysis using ImageNet

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey

Breast Tissue Composition and Susceptibility to Breast Cancer

Representation learning for mammography mass lesion classification with convolutional neural networks

Exploring feature-based approaches in PET images for predicting cancer treatment outcomes

Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer

Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system

Cancer of the Breast

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation

Why illness perceptions matter