Wajdi Alghamdi

Orcid: 0000-0002-7999-2561

According to our database1, Wajdi Alghamdi authored at least 17 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
VEGF-ERCNN: A deep learning-based model for prediction of vascular endothelial growth factor using ensemble residual CNN.
J. Comput. Sci., 2024

IP-GCN: A deep learning model for prediction of insulin using graph convolutional network for diabetes drug design.
J. Comput. Sci., 2024

2023
A new deep boosted CNN and ensemble learning based IoT malware detection.
Comput. Secur., October, 2023

AFP-SPTS: An Accurate Prediction of Antifreeze Proteins Using Sequential and Pseudo-Tri-Slicing Evolutionary Features with an Extremely Randomized Tree.
J. Chem. Inf. Model., February, 2023

2022
DBP-CNN: Deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network.
Expert Syst. Appl., 2022

Structure preserving loss function for single image super resolution.
Displays, 2022

LBCEPred: a machine learning model to predict linear B-cell epitopes.
Briefings Bioinform., 2022

Semi-Supervised Skin Lesion Segmentation With Coupling CNN and Transformer Features.
IEEE Access, 2022

2018
Predictive modelling approach to data-driven computational psychiatry.
PhD thesis, 2018

Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, 2018

Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use?
Proceedings of the Artificial Intelligence Applications and Innovations, 2018

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches.
Proceedings of the Artificial Intelligence Applications and Innovations, 2018

A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis.
Proceedings of the Health Informatics Meets eHealth - Biomedical Meets eHealth - From Sensors to Decisions, 2018

2017
Swarmic approach for symmetry detection of cellular automata behaviour.
Soft Comput., 2017

Predicting Psychosis Using the Experience Sampling Method with Mobile Apps.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

2016
A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016


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