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A novel autoencoder-based diagnostic system for early assessment of lung cancer
(IEEE, 2018-07)
A novel framework for the classification of lung nodules using computed tomography (CT) scans is proposed in this paper. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the ...
Athlete-customized injury prediction using training load statistical records and machine learning
(IEEE, 2018)
The management of athletic performance is of immense importance in the sports industry. Performance management is concerned with maximizing athletes' performance and minimizing the risk of player injuries. Several factors ...
A Machine Learning Approach for Self-Diagnosing Multiprocessors Systems under the Generalized Comparison Model
(IEEE, 2014-01)
Support Vector Machines (SVMs) have been successfully applied to pattern recognition, regression, and classification. Because of their good performance and their mathematical foundations, SVMs are gaining popularity in ...
Prediction of therapeutic peptides using machine learning: computational models, datasets, and feature encodings
(IEEE, 2020-08)
Peptides, short-chained amino acids, have shown great potentials toward the investigation and evolution of novel medications for treatment or therapy. The wet-lab based discovery of potential therapeutic peptides and ...
Autism Classification Using SMRI: A Recursive Features Selection Based on Sampling from Multi-Level High Dimensional Spaces
(IEEE, 2021-04)
Autism spectrum disorder (ASD) can be described as a cognitive and behavioral impairment associated with a group of polygenetic brain disorders. ASD affects 1.4% of the children in the population. Structural MRI (sMRI) has ...
A systematic literature review on hardware implementation of artificial intelligence algorithms
(Springer US, 2021-12)
Artificial intelligence (AI) and machine learning (ML) tools play a significant role in the recent evolution of smart systems. AI solutions are pushing towards a significant shift in many fields such as healthcare, autonomous ...
Artificial intelligence applications in solid waste management: A systematic research review
(Pergamon, 2020-05)
The waste management processes typically involve numerous technical, climatic, environmental, demographic, socio-economic, and legislative parameters. Such complex nonlinear processes are challenging to model, predict and ...
A systematic literature review on hardware implementation of artificial intelligence algorithms
(Springer US, 2021-02)
Artificial intelligence (AI) and machine learning (ML) tools play a significant role in the recent evolution of smart systems. AI solutions are pushing towards a significant shift in many fields such as healthcare, autonomous ...
Machine learning for anomaly detection: a systematic review
(IEEE, 2021-05)
Anomaly detection has been used for decades to identify and extract anomalous components from data. Many techniques have been used to detect anomalies. One of the increasingly significant techniques is Machine Learning ...
Machine learning classifications of coronary artery disease
(IEEE, 2018-11)
Coronary Artery Disease (CAD) is one of the leading causes of death worldwide, and so it is very important to correctly diagnose patients with the disease. For medical diagnosis, machine learning is a useful tool; however ...