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Alle Papers – KI in der Krebserkennung

172.746 Papers insgesamt · Seite 63 von 400

1551.

Recognition of peripheral blood cell images using convolutional neural networks

2019·212 Zit.·Computer Methods and Programs in Biomedicine
1552.

Artificial Intelligence in Dermatology Image Analysis: Current Developments and Future Trends

2022·212 Zit.·Journal of Clinical MedicineOA
1553.

Clinical Validation of the cobas 4800 HPV Test for Cervical Screening Purposes

2011·212 Zit.·Journal of Clinical MicrobiologyOA
1554.

Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images

1995·211 Zit.·IEEE Transactions on Medical Imaging
1555.

On breast cancer detection

2018·211 Zit.
1556.

The Positive Predictive Value of BI-RADS Microcalcification Descriptors and Final Assessment Categories

2010·211 Zit.·American Journal of Roentgenology
1557.

Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology

2016·211 Zit.·Computerized Medical Imaging and GraphicsOA
1558.

Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis

2019·211 Zit.·Trends in cancer
1559.

Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms

2016·211 Zit.·Journal of Medical Systems
1560.

Comparison of a virtual microscope laboratory to a regular microscope laboratory for teaching histology

2001·211 Zit.·The Anatomical Record
1561.

Effectiveness of Digital Breast Tomosynthesis Compared With Digital Mammography

2016·211 Zit.·JAMA OncologyOA
1562.

A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks

2020·211 Zit.·IEEE AccessOA
1563.

Machine Learning Classification Techniques for Breast Cancer Diagnosis

2019·211 Zit.·IOP Conference Series Materials Science and EngineeringOA
1564.

Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study

2019·211 Zit.·European RadiologyOA
1565.

Automatic Identification of the Pectoral Muscle in Mammograms

2004·211 Zit.·IEEE Transactions on Medical Imaging
1566.

Using deep learning to segment breast and fibroglandular tissue in MRI volumes

2016·211 Zit.·Medical PhysicsOA
1567.

Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning

2021·211 Zit.·Nature CommunicationsOA
1568.

Artificial neural networks for diagnosis and survival prediction in colon cancer

2005·211 Zit.·Molecular CancerOA
1569.

Mobile teledermatology for skin tumour screening: diagnostic accuracy of clinical and dermoscopic image tele-evaluation using cellular phones

2011·210 Zit.·British Journal of Dermatology
1570.

A Framework for Medical Image Retrieval Using Machine Learning and Statistical Similarity Matching Techniques With Relevance Feedback

2007·210 Zit.·IEEE Transactions on Information Technology in Biomedicine
1571.

Lymphatic Mapping and Sentinel Lymph Node Biopsy in Patients With Melanoma: A Meta-Analysis

2011·210 Zit.·Journal of Clinical OncologyOA
1572.

Histologic subtype classification of non-small cell lung cancer using PET/CT images

2020·210 Zit.·European Journal of Nuclear Medicine and Molecular Imaging
1573.

Virtual microscopy in pathology education

2009·210 Zit.·Human Pathology
1574.

The state of the art of deep learning models in medical science and their challenges

2020·210 Zit.·Multimedia Systems
1575.

Retrospective Cost-effectiveness Analysis of Screening Mammography

2006·210 Zit.·JNCI Journal of the National Cancer InstituteOA