Deep learning with graph convolutional networks: An overview and latest applications in computational intelligence
Convolutional neural networks (CNNs) have received widespread attention due to their
powerful modeling capabilities and have been successfully applied in natural language …
powerful modeling capabilities and have been successfully applied in natural language …
Graph-based deep learning for medical diagnosis and analysis: past, present and future
With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …
problems have been tackled. It has become critical to explore how machine learning and …
An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm
EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2022 - Springer
Breast cancer is the second leading cause of death in women; therefore, effective early
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
[HTML][HTML] Facial expression recognition via ResNet-50
B Li, D Lima - International Journal of Cognitive Computing in …, 2021 - Elsevier
As one of the most important directions in the field of computer vision, facial emotion
recognition plays an important role in people's daily work and life. Human emotion …
recognition plays an important role in people's daily work and life. Human emotion …
Classification of breast cancer using transfer learning and advanced al-biruni earth radius optimization
Breast cancer is one of the most common cancers in women, with an estimated 287,850 new
cases identified in 2022. There were 43,250 female deaths attributed to this malignancy. The …
cases identified in 2022. There were 43,250 female deaths attributed to this malignancy. The …
High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets
Breast cancer is a significant cause of cancer fatality among women all over the world.
Hence the detection of this disease at the initial stage works as a boon to the patient so that …
Hence the detection of this disease at the initial stage works as a boon to the patient so that …
SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network
COVID-19 has emerged as one of the deadliest pandemics that has ever crept on humanity.
Screening tests are currently the most reliable and accurate steps in detecting severe acute …
Screening tests are currently the most reliable and accurate steps in detecting severe acute …
An enhanced Predictive heterogeneous ensemble model for breast cancer prediction
Breast Cancer is one of the most prevalent tumors after lung cancer and is common in both
women and men. This disease is mostly asymptomatic in the early stages thus detection is …
women and men. This disease is mostly asymptomatic in the early stages thus detection is …
A survey on parameter identification, state estimation and data analytics for lateral flow immunoassay: from systems science perspective
Lateral flow immunoassay (LFIA), as a well-known point-of-care testing (POCT) technique, is
of vital significance in a variety of application scenarios due to the advantages of …
of vital significance in a variety of application scenarios due to the advantages of …
EEG emotion recognition using improved graph neural network with channel selection
X Lin, J Chen, W Ma, W Tang, Y Wang - Computer Methods and Programs …, 2023 - Elsevier
Background and objective: Emotion classification tasks based on electroencephalography
(EEG) are an essential part of artificial intelligence, with promising applications in healthcare …
(EEG) are an essential part of artificial intelligence, with promising applications in healthcare …