Alle Papers – KI in der Krebserkennung
172.746 Papers insgesamt · Seite 91 von 400
A review of original articles published in the emerging field of radiomics
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
Glomerulosclerosis identification in whole slide images using semantic segmentation
Channel Attention Module with Multi-scale Grid Average Pooling for Breast Cancer Segmentation in an Ultrasound Image
Weakly supervised mitosis detection in breast histopathology images using concentric loss
Improved Cancer Detection Using Computer-Aided Detection with Diagnostic and Screening Mammography: Prospective Study of 104 Cancers
Risk Factors for Cutaneous Melanoma in Queensland
Telepathology and the networking of pathology diagnostic services.
Abnormal breast identification by nine-layer convolutional neural network with parametric rectified linear unit and rank-based stochastic pooling
MLCA2F: Multi-Level Context Attentional Feature Fusion for COVID-19 lesion segmentation from CT scans
Intelligent Model to Predict Early Liver Disease using Machine Learning Technique
A statistical 3-D pattern processing method for computer-aided detection of polyps in CT colonography
A new classifier for breast cancer detection based on Naïve Bayesian
Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study
Machine learning techniques to diagnose breast cancer
A Review of Breast Ultrasound
Classification of COVID-19 from Chest X-ray images using Deep Convolutional Neural Network
HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation
Pancreatic Cancer Prediction Through an Artificial Neural Network
COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization
Automatic detection of oral cancer in smartphone-based images using deep learning for early diagnosis
Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images
Image set for deep learning: field images of maize annotated with disease symptoms
Accurate Prediction of COVID-19 using Chest X-Ray Images through Deep Feature Learning model with SMOTE and Machine Learning Classifiers
Histopathologic Technic