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Alle Papers – KI in der Krebserkennung

168.310 Papers insgesamt · Seite 16 von 400

376.

How to Read Articles That Use Machine Learning

2019·507 Zit.·JAMA
377.

BI-RADS Lexicon for US and Mammography: Interobserver Variability and Positive Predictive Value

2006·506 Zit.·Radiology
378.

A deep learning model to predict RNA-Seq expression of tumours from whole slide images

2020·505 Zit.·Nature CommunicationsOA
379.

Artificial intelligence and computational pathology

2021·504 Zit.·Laboratory InvestigationOA
380.

Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide

2019·503 Zit.·Radiology
381.

Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

2020·503 Zit.·The Lancet Digital HealthOA
382.

The Bethesda System for Reporting Thyroid Cytopathology

2010·503 Zit.
383.

Deep learning for image-based cancer detection and diagnosis − A survey

2018·501 Zit.·Pattern Recognition
384.

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification

2021·501 Zit.·arXiv (Cornell University)OA
385.

Application of deep transfer learning for automated brain abnormality classification using MR images

2018·500 Zit.·Cognitive Systems Research
386.

<title>Nuclear feature extraction for breast tumor diagnosis</title>

1993·500 Zit.·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
387.

Local binary patterns variants as texture descriptors for medical image analysis

2010·497 Zit.·Artificial Intelligence in Medicine
388.

Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network

2019·496 Zit.·IEEE Transactions on Neural Networks and Learning SystemsOA
389.

A new era: artificial intelligence and machine learning in prostate cancer

2019·496 Zit.·Nature Reviews Urology
390.

An expert system for detection of breast cancer based on association rules and neural network

2008·495 Zit.·Expert Systems with Applications
391.

Breast cancer detection using automated whole breast ultrasound and mammography in radiographically dense breasts

2009·495 Zit.·European RadiologyOA
392.

Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data

2012·495 Zit.·IEEE Transactions on Pattern Analysis and Machine Intelligence
393.

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

2016·493 Zit.·arXiv (Cornell University)OA
394.

Deep Learning and Medical Diagnosis: A Review of Literature

2018·493 Zit.·Multimodal Technologies and InteractionOA
395.

All-IDB: The acute lymphoblastic leukemia image database for image processing

2011·491 Zit.OA
396.

Quantitative Assessment of Mammographic Breast Density: Relationship with Breast Cancer Risk

2004·491 Zit.·Radiology
397.

Artificial intelligence and machine learning in clinical development: a translational perspective

2019·490 Zit.·npj Digital MedicineOA
398.

NAS-Unet: Neural Architecture Search for Medical Image Segmentation

2019·490 Zit.·IEEE AccessOA
399.

Breast cancer detection using deep convolutional neural networks and support vector machines

2019·489 Zit.·PeerJOA
400.

Beyond imaging: The promise of radiomics

2017·488 Zit.·Physica Medica