Luca Parisi
Orcid: 0000-0002-5865-8708
According to our database1,
Luca Parisi
authored at least 19 papers
between 2016 and 2025.
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Bibliography
2025
Optimal Machine Learning- and Deep Learning-driven algorithms for predicting the future value of investments: A systematic review and meta-analysis.
Eng. Appl. Artif. Intell., 2025
2024
Knowl. Based Syst., 2024
A Transfer Learning-Based Approach to Unveil Kinase-Specific Phosphorylation Sites of Understudied Kinases.
Proceedings of the Bioinformatics and Biomedical Engineering, 2024
A Novel Artificial Intelligence-Driven Technique for Enhancing Medical Imaging Techniques to Detect Non-Small Cell Lung Cancer.
Proceedings of the 12th European Workshop on Visual Information Processing, 2024
2023
Innovative feature-driven machine learning and deep learning for finance, education, and healthcare.
Neural Comput. Appl., June, 2023
Holistic similarity-based prediction of phosphorylation sites for understudied kinases.
Briefings Bioinform., March, 2023
2022
Neural Process. Lett., 2022
Quantum ReLU activation for Convolutional Neural Networks to improve diagnosis of Parkinson's disease and COVID-19.
Expert Syst. Appl., 2022
Neuroevolutionary intelligent system to aid diagnosis of motor impairments in children.
Appl. Intell., 2022
2021
2020
Neural Process. Lett., 2020
A novel hybrid algorithm for aiding prediction of prognosis in patients with hepatitis.
Neural Comput. Appl., 2020
Knowl. Based Syst., 2020
hyper-sinh: An Accurate and Reliable Function from Shallow to Deep Learning in TensorFlow and Keras.
CoRR, 2020
QReLU and m-QReLU: Two novel quantum activation functions to aid medical diagnostics.
CoRR, 2020
CoRR, 2020
2018
Decision support system to improve postoperative discharge: A novel multi-class classification approach.
Knowl. Based Syst., 2018
Expert Syst. Appl., 2018
2016
Towards a Software Product Line for Machine Learning Workflows: Focus on Supporting Evolution.
Proceedings of the 10th Workshop on Models and Evolution co-located with ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems (MODELS 2016), 2016