[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …
grows, especially in high-stakes decision making areas such as medical image analysis …
[HTML][HTML] Transparency of deep neural networks for medical image analysis: A review of interpretability methods
Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
Explainable deep learning models in medical image analysis
Deep learning methods have been very effective for a variety of medical diagnostic tasks
and have even outperformed human experts on some of those. However, the black-box …
and have even outperformed human experts on some of those. However, the black-box …
Multi-classification of brain tumor MRI images using deep convolutional neural network with fully optimized framework
E Irmak - Iranian Journal of Science and Technology …, 2021 - Springer
Brain tumor diagnosis and classification still rely on histopathological analysis of biopsy
specimens today. The current method is invasive, time-consuming and prone to manual …
specimens today. The current method is invasive, time-consuming and prone to manual …
On the interpretability of artificial intelligence in radiology: challenges and opportunities
As artificial intelligence (AI) systems begin to make their way into clinical radiology practice,
it is crucial to assure that they function correctly and that they gain the trust of experts …
it is crucial to assure that they function correctly and that they gain the trust of experts …
A survey on explainable artificial intelligence (xai): Toward medical xai
Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …
remarkable performances in many tasks, from image processing to natural language …
Classification of brain tumors from MRI images using a convolutional neural network
MM Badža, MČ Barjaktarović - Applied Sciences, 2020 - mdpi.com
The classification of brain tumors is performed by biopsy, which is not usually conducted
before definitive brain surgery. The improvement of technology and machine learning can …
before definitive brain surgery. The improvement of technology and machine learning can …
Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …
recognition is a challenging problem for radiologists in health monitoring and automated …
[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …
diagnosis with their outstanding image classification performance. In spite of the outstanding …
Deep learning for medical anomaly detection–a survey
Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …
extensively studied. Numerous approaches have been proposed across various medical …