Alle Papers – KI in der Krebserkennung

AI applications in robotics, diagnostic image analysis and precision medicine: Current limitations, future trends, guidelines on CAD systems for medicine

Generative adversarial networks and synthetic patient data: current challenges and future perspectives

Digital Breast Tomosynthesis: A Pilot Observer Study

Mammographic signs as risk factors for breast cancer

Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data

Infrared Imaging of the Breast: Initial Reappraisal Using High-Resolution Digital Technology in 100 Successive Cases of Stage I and II Breast Cancer

Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images

Virtual microscopy and digital pathology in training and education

Knowledge transfer for melanoma screening with deep learning

Analysis of asymmetry in mammograms via directional filtering with Gabor wavelets

Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images—The ACDC@LungHP Challenge 2019

DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation

An integrated iterative annotation technique for easing neural network training in medical image analysis

Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images

Morphological and molecular breast cancer profiling through explainable machine learning

RETRACTED ARTICLE: Early diagnosis of COVID-19-affected patients based on X-ray and computed tomography images using deep learning algorithm

Detection of cervical cancer cells based on strong feature CNN-SVM network

Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM)

A hybrid explainable ensemble transformer encoder for pneumonia identification from chest X-ray images

A DE-ANN Inspired Skin Cancer Detection Approach Using Fuzzy C-Means Clustering

A Comprehensive Review on Breast Cancer Detection, Classification and Segmentation Using Deep Learning

Weakly supervised machine learning

A Probabilistic U-Net for Segmentation of Ambiguous Images

Hybrid CNN and XGBoost Model Tuned by Modified Arithmetic Optimization Algorithm for COVID-19 Early Diagnostics from X-ray Images

Changes in Recall Type and Patient Treatment Following Implementation of Screening Digital Breast Tomosynthesis