Diagnosis of COVID-19 using machine learning and deep learning: a review
Background: This paper provides a systematic review of the application of Artificial
Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in …
Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in …
A Machine Learning‐Based Big EEG Data Artifact Detection and Wavelet‐Based Removal: An Empirical Approach
The electroencephalogram (EEG) signals are a big data which are frequently corrupted by
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
A survey on multi-objective hyperparameter optimization algorithms for machine learning
A Morales-Hernández, I Van Nieuwenhuyse… - Artificial Intelligence …, 2023 - Springer
Hyperparameter optimization (HPO) is a necessary step to ensure the best possible
performance of Machine Learning (ML) algorithms. Several methods have been developed …
performance of Machine Learning (ML) algorithms. Several methods have been developed …
Densely connected convolutional networks-based COVID-19 screening model
The extensively utilized tool to detect novel coronavirus (COVID-19) is a real-time
polymerase chain reaction (RT-PCR). However, RT-PCR kits are costly and consume critical …
polymerase chain reaction (RT-PCR). However, RT-PCR kits are costly and consume critical …
A review paper about deep learning for medical image analysis
B Sistaninejhad, H Rasi, P Nayeri - … and Mathematical Methods …, 2023 - Wiley Online Library
Medical imaging refers to the process of obtaining images of internal organs for therapeutic
purposes such as discovering or studying diseases. The primary objective of medical image …
purposes such as discovering or studying diseases. The primary objective of medical image …
A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing …
Background and objective COVID-19 outbreak has become one of the most challenging
problems for human being. It is a communicable disease caused by a new coronavirus …
problems for human being. It is a communicable disease caused by a new coronavirus …
Integrated CNN and federated learning for COVID-19 detection on chest X-ray images
Z Li, X Xu, X Cao, W Liu, Y Zhang… - … /ACM Transactions on …, 2022 - ieeexplore.ieee.org
Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and
safety and deep learning (DL) is expected to be the most powerful method for efficient …
safety and deep learning (DL) is expected to be the most powerful method for efficient …
Text‐Based Emotion Recognition Using Deep Learning Approach
SK Bharti, S Varadhaganapathy… - Computational …, 2022 - Wiley Online Library
Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions
towards a given goal, such as people, activities, organizations, services, subjects, and …
towards a given goal, such as people, activities, organizations, services, subjects, and …
Recurrent neural network and reinforcement learning model for COVID-19 prediction
Detection and prediction of the novel Coronavirus present new challenges for the medical
research community due to its widespread across the globe. Methods driven by Artificial …
research community due to its widespread across the globe. Methods driven by Artificial …
A wavelet-based deep learning pipeline for efficient COVID-19 diagnosis via CT slices
O Attallah, A Samir - Applied Soft Computing, 2022 - Elsevier
The quick diagnosis of the novel coronavirus (COVID-19) disease is vital to prevent its
propagation and improve therapeutic outcomes. Computed tomography (CT) is believed to …
propagation and improve therapeutic outcomes. Computed tomography (CT) is believed to …