A systematic literature review of medical image analysis using deep learning
R Buettner, M Bilo, N Bay… - 2020 IEEE Symposium on …, 2020 - ieeexplore.ieee.org
We review literature in top journals and conferences on the usage of deep learning for
medical image analysis in modern healthcare. As a result it is shown that deep learning …
medical image analysis in modern healthcare. As a result it is shown that deep learning …
An analysis of image features extracted by CNNs to design classification models for COVID-19 and non-COVID-19
The SARS-CoV-2 virus causes a respiratory disease in humans, known as COVID-19. The
confirmatory diagnostic of this disease occurs through the real-time reverse transcription and …
confirmatory diagnostic of this disease occurs through the real-time reverse transcription and …
Adpt: An automated disease prognosis tool towards classifying medical disease using hybrid architecture of deep learning paradigm
S Al Jannat, A Amin, MS Hossain… - … on Computer and …, 2022 - ieeexplore.ieee.org
The Covid 19 beta coronavirus, commonly known as the severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), is currently one of the most significant RNA-type viruses in …
coronavirus 2 (SARS-CoV-2), is currently one of the most significant RNA-type viruses in …
[PDF][PDF] Deep feedforward neural network classifier with polynomial layer and shared weights
K Filippou, G Aifantis, E Mavrikos… - Advances in Signal …, 2022 - researchgate.net
This paper introduces a novel deep feedforward neural network to perform classification
tasks. The network encompasses several dense hidden layers followed by a polynomial …
tasks. The network encompasses several dense hidden layers followed by a polynomial …