Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
Covid-caps: A capsule network-based framework for identification of covid-19 cases from x-ray images
P Afshar, S Heidarian, F Naderkhani… - Pattern Recognition …, 2020 - Elsevier
Abstract Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …
MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques
Background Detecting brain tumors in their early stages is crucial. Brain tumors are
classified by biopsy, which can only be performed through definitive brain surgery …
classified by biopsy, which can only be performed through definitive brain surgery …
[HTML][HTML] An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning
Brain tumors are among the most fatal and devastating diseases, often resulting in
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …
Deep convolutional neural network based medical image classification for disease diagnosis
Medical image classification plays an essential role in clinical treatment and teaching tasks.
However, the traditional method has reached its ceiling on performance. Moreover, by using …
However, the traditional method has reached its ceiling on performance. Moreover, by using …
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 …
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 …
A deep learning approach for brain tumor classification using MRI images
Brain tumors can be fatal if not detected early enough. Manually diagnosing brain tumors
requires the radiologist's experience and expertise, which may not always be available …
requires the radiologist's experience and expertise, which may not always be available …
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 …
Secure and robust machine learning for healthcare: A survey
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning
(DL) techniques due to their superior performance for a variety of healthcare applications …
(DL) techniques due to their superior performance for a variety of healthcare applications …