Alle Papers – KI in der Krebserkennung

Explainable artificial intelligence in skin cancer recognition: A systematic review

Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and ‐SNE

Segmentation of fingerprint images using the directional image

Computer aids and human second reading as interventions in screening mammography: Two systematic reviews to compare effects on cancer detection and recall rate

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Radiomic features analysis in computed tomography images of lung nodule classification

Pap smear diagnosis using a hybrid intelligent scheme focusing on genetic algorithm based feature selection and nearest neighbor classification

Association of Volume and Volume-Independent Factors With Accuracy in Screening Mammogram Interpretation

Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN)

Deep Learning: An Update for Radiologists

Comparative Accuracy of Mammography and Ultrasound in Women with Breast Symptoms According to Age and Breast Density

The challenge of early detection in cancer

Collective Intelligence Meets Medical Decision-Making: The Collective Outperforms the Best Radiologist

A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer

Novel Approaches to Screening for Breast Cancer

A three-dimensional breast software phantom for mammography simulation

Melanoma image classification based on MobileNetV2 network

Generation and evaluation of privacy preserving synthetic health data

A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database

Artificial Intelligence in Medical Imaging

Digital image analysis for diagnosis of cutaneous melanoma. Development of a highly effective computer algorithm based on analysis of 837 melanocytic lesions

COVID faster R–CNN: A novel framework to Diagnose Novel Coronavirus Disease (COVID-19) in X-Ray images

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging

Improved Threshold Based and Trainable Fully Automated Segmentation for Breast Cancer Boundary and Pectoral Muscle in Mammogram Images

Skin cancer detection using ensemble of machine learning and deep learning techniques