Alle Papers – KI in der Krebserkennung

A deep look into radiomics

DeepPap: Deep Convolutional Networks for Cervical Cell Classification

Medical image analysis using deep learning algorithms

Automatic recognition of five types of white blood cells in peripheral blood

Benign and malignant breast tumors classification based on region growing and CNN segmentation

Diagnosis of Pneumonia from Chest X-Ray Images Using Deep Learning

An enhanced technique of skin cancer classification using deep convolutional neural network with transfer learning models

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Cancer Yield of Mammography, MR, and US in High-Risk Women: Prospective Multi-Institution Breast Cancer Screening Study

Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images

A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique

Diagnostic Inaccuracy of Smartphone Applications for Melanoma Detection

AfterQC: automatic filtering, trimming, error removing and quality control for fastq data

Deep neural networks are superior to dermatologists in melanoma image classification

Are Pretreatment ¹⁸F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy?

The Danish Pathology Register

Predicting outcomes in radiation oncology—multifactorial decision support systems

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer’s Disease Diagnosis

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets

BI-RADS Categorization As a Predictor of Malignancy

An Evidence-based Staging System for Cutaneous Melanoma

Medical image classification using synergic deep learning

OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects

An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening

The Current and Future State of AI Interpretation of Medical Images