Towards a Software Product Line for Machine Learning Workflows: Focus on Supporting Evolution. - Cécile Camillieri; Luca Parisi; Mireille Blay-Fornarino; Frédéric Precioso; Michel Riveill; Joël Cancela Vaz (ME@MoDELS, 2016)

Feature-driven machine learning to improve early diagnosis of Parkinson's disease. - Luca Parisi; Narrendar RaviChandran; Marianne Lyne Manaog (Expert Syst. Appl., 2018)

Decision support system to improve postoperative discharge: A novel multi-class classification approach. - Luca Parisi; Narrendar RaviChandran; Marianne Lyne Manaog (Knowl. Based Syst., 2018)

m-arcsinh: An Efficient and Reliable Function for SVM and MLP in scikit-learn. - Luca Parisi (CoRR, 2020)

QReLU and m-QReLU: Two novel quantum activation functions to aid medical diagnostics. - Luca Parisi; Daniel Neagu; Renfei Ma; Felician Campean (CoRR, 2020)

hyper-sinh: An Accurate and Reliable Function from Shallow to Deep Learning in TensorFlow and Keras. - Luca Parisi; Renfei Ma; Narrendar RaviChandran; Matteo Lanzillotta (CoRR, 2020)

Evolutionary feature transformation to improve prognostic prediction of hepatitis. - Luca Parisi; Narrendar RaviChandran (Knowl. Based Syst., 2020)

A novel hybrid algorithm for aiding prediction of prognosis in patients with hepatitis. - Luca Parisi; Narrendar RaviChandran; Marianne Lyne Manaog (Neural Comput. Appl., 2020)

Evolutionary Denoising-Based Machine Learning for Detecting Knee Disorders. - Luca Parisi; Narrendar RaviChandran (Neural Process. Lett., 2020)

M-ar-K-Fast Independent Component Analysis. - Luca Parisi (CoRR, 2021)

Neuroevolutionary intelligent system to aid diagnosis of motor impairments in children. - Matteo Lanzillotta; Renfei Ma; Marcella Accardi; Narrendar RaviChandran; Amir Zaernia; Mansour Youseffi; Luca Parisi (Appl. Intell., 2022)

Quantum ReLU activation for Convolutional Neural Networks to improve diagnosis of Parkinson's disease and COVID-19. - Luca Parisi; Daniel Neagu; Renfei Ma; Felician Campean (Expert Syst. Appl., 2022)

Syncretic Feature Selection for Machine Learning-Aided Prognostics of Hepatitis. - Luca Parisi; Narrendar RaviChandran (Neural Process. Lett., 2022)

A Physiologically Informed Three-Dimensional Convolutional Neural Network to Aid Diagnosis of Non-Small Cell Lung Cancer. - Amir Zaernia; Mansour Youseffi; Luca Parisi (ICECET, 2023)

Holistic similarity-based prediction of phosphorylation sites for understudied kinases. - Renfei Ma; Shangfu Li; Luca Parisi; Wenshuo Li; Hsien-Da Huang; Tzong-Yi Lee (Briefings Bioinform., 2023)

Innovative feature-driven machine learning and deep learning for finance, education, and healthcare. - Luca Parisi; Marianne Lyne Manaog (Neural Comput. Appl., 2023)

A Novel Artificial Intelligence-Driven Technique for Enhancing Medical Imaging Techniques to Detect Non-Small Cell Lung Cancer. - Amir Zaernia; Mansour Youseffi; Luca Parisi; Raed Abd-Alhameed; Renfei Ma (EUVIP, 2024)

A Transfer Learning-Based Approach to Unveil Kinase-Specific Phosphorylation Sites of Understudied Kinases. - Wentao Huang; Xiaoyan Zhou; Luca Parisi; Mansour Youseffi; Renfei Ma (IWBBIO (2), 2024)

Optimal evolutionary framework-based activation function for image classification. - Luca Parisi; Ciprian-Daniel Neagu; Narrendar RaviChandran; Renfei Ma; Felician Campean (Knowl. Based Syst., 2024)

A novel integrative multimodal classifier to enhance the diagnosis of Parkinson's disease. - Xiaoyan Zhou; Luca Parisi; Wentao Huang; Yihan Zhang; Xiaoqun Huang; Mansour Youseffi; Farideh Javid; Renfei Ma (Briefings Bioinform., 2025)

Optimal Machine Learning- and Deep Learning-driven algorithms for predicting the future value of investments: A systematic review and meta-analysis. - Luca Parisi; Marianne Lyne Manaog (Eng. Appl. Artif. Intell., 2025)