Alle Papers – KI in der Krebserkennung

Mammographic density and breast cancer risk: current understanding and future prospects

Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer

Machine Learning in Medical Imaging

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Adapting to Artificial Intelligence

A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data

An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

Influence of Computer-Aided Detection on Performance of Screening Mammography

A visual-language foundation model for computational pathology

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study

3D Deep Learning on Medical Images: A Review

Variability in Radiologists' Interpretations of Mammograms

Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation

Transformer-based unsupervised contrastive learning for histopathological image classification

Diffusion models in medical imaging: A comprehensive survey

Missing data imputation using statistical and machine learning methods in a real breast cancer problem

Validating Whole Slide Imaging for Diagnostic Purposes in Pathology: Guideline from the College of American Pathologists Pathology and Laboratory Quality Center

A review on deep learning in medical image analysis

Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System

Deep learning in biomedicine

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks

Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation

The Clinician and Dataset Shift in Artificial Intelligence