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A comprehensive review on breast cancer detection, classification and segmentation using deep learning
The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review
EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021 - Elsevier
Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …
can help decrease breast cancer mortality rates. Computer-aided detection allows …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Artificial intelligence in cancer research, diagnosis and therapy
Artificial intelligence and machine learning techniques are breaking into biomedical
research and health care, which importantly includes cancer research and oncology, where …
research and health care, which importantly includes cancer research and oncology, where …
A guide to deep learning in healthcare
Here we present deep-learning techniques for healthcare, centering our discussion on deep
learning in computer vision, natural language processing, reinforcement learning, and …
learning in computer vision, natural language processing, reinforcement learning, and …
Convolutional neural networks: an overview and application in radiology
Convolutional neural network (CNN), a class of artificial neural networks that has become
dominant in various computer vision tasks, is attracting interest across a variety of domains …
dominant in various computer vision tasks, is attracting interest across a variety of domains …
Designing deep learning studies in cancer diagnostics
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
Stand-alone artificial intelligence for breast cancer detection in mammography: comparison with 101 radiologists
A Rodriguez-Ruiz, K Lång… - JNCI: Journal of the …, 2019 - academic.oup.com
Background Artificial intelligence (AI) systems performing at radiologist-like levels in the
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …
Artificial intelligence in radiology
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …
Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …