Alle Papers – KI in der Krebserkennung
168.310 Papers insgesamt · Seite 16 von 400
How to Read Articles That Use Machine Learning
BI-RADS Lexicon for US and Mammography: Interobserver Variability and Positive Predictive Value
A deep learning model to predict RNA-Seq expression of tumours from whole slide images
Artificial intelligence and computational pathology
Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide
Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study
The Bethesda System for Reporting Thyroid Cytopathology
Deep learning for image-based cancer detection and diagnosis − A survey
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
Application of deep transfer learning for automated brain abnormality classification using MR images
<title>Nuclear feature extraction for breast tumor diagnosis</title>
Local binary patterns variants as texture descriptors for medical image analysis
Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network
A new era: artificial intelligence and machine learning in prostate cancer
An expert system for detection of breast cancer based on association rules and neural network
Breast cancer detection using automated whole breast ultrasound and mammography in radiographically dense breasts
Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Deep Learning and Medical Diagnosis: A Review of Literature
All-IDB: The acute lymphoblastic leukemia image database for image processing
Quantitative Assessment of Mammographic Breast Density: Relationship with Breast Cancer Risk
Artificial intelligence and machine learning in clinical development: a translational perspective
NAS-Unet: Neural Architecture Search for Medical Image Segmentation
Breast cancer detection using deep convolutional neural networks and support vector machines
Beyond imaging: The promise of radiomics