Alle Papers – KI in der Krebserkennung

Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis

Breast Cancer Detection Using Machine Learning Algorithms

Computer-aided diagnosis in radiology: potential and pitfalls

If You Don’t Find It Often, You Often Don’t Find It: Why Some Cancers Are Missed in Breast Cancer Screening

Artificial intelligence in reproductive medicine

A Multifactorial Model for Pancreatic Cancer in Man

STACS: new active contour scheme for cardiac MR image segmentation

The Performance of MelaFind

Analysis Of Ultrasound Image Texture Via Generalized Rician Statistics

Multi-Instance Deep Learning: Discover Discriminative Local Anatomies for Bodypart Recognition

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers

High Incidence of Prostate Cancer Detected by Saturation Biopsy after Previous Negative Biopsy Series

Computer Recognition of Regional Lung Disease Patterns

Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions

Clinical Significance of Immunocytochemical Detection of Tumor Cells Using Digital Microscopy in Peripheral Blood and Bone Marrow of Breast Cancer Patients

AUTOMATED GRADING OF PROSTATE CANCER USING ARCHITECTURAL AND TEXTURAL IMAGE FEATURES

A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI

MedSegDiff-V2: Diffusion-Based Medical Image Segmentation with Transformer

Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests

Automatic lung cancer detection from CT image using improved deep neural network and ensemble classifier

Randomized Trial of Screen-Film versus Full-Field Digital Mammography with Soft-Copy Reading in Population-based Screening Program: Follow-up and Final Results of Oslo II Study

LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation

Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning

Deep learning for colon cancer histopathological images analysis

Skin lesion classification of dermoscopic images using machine learning and convolutional neural network