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ORCIDDavide Chicco
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- affiliation: University of Toronto, Institute of Health Policy Management and Evaluation, ON, Canada
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Books and Theses
- 2014
[b1]Davide Chicco:
Computational Prediction of Gene Functions through Machine Learning methods and Multiple Validation Procedures. Polytechnic University of Milan, Italy, 2014
Journal Articles
- 2024
- [j36]Gabriel Cerono
, Ombretta Melaiu, Davide Chicco:
Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme. J. Heal. Informatics Res. 8(1): 1-18 (2024) - [j35]Gabriel Cerono, Davide Chicco:
Ensemble machine learning reveals key features for diabetes duration from electronic health records. PeerJ Comput. Sci. 10: e1896 (2024) - 2023
- [j34]Davide Chicco, Giuseppe Jurman:
Ten simple rules for providing bioinformatics support within a hospital. BioData Min. 16(1) (2023) - [j33]Davide Chicco, Giuseppe Jurman:
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData Min. 16(1) (2023) - [j32]Davide Chicco, Tiziana Sanavia, Giuseppe Jurman:
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. BioData Min. 16(1) (2023) - [j31]Davide Chicco, Giuseppe Jurman:
A statistical comparison between Matthews correlation coefficient (MCC), prevalence threshold, and Fowlkes-Mallows index. J. Biomed. Informatics 144: 104426 (2023) - [j30]Davide Chicco, Rakesh Shiradkar:
Ten quick tips for computational analysis of medical images. PLoS Comput. Biol. 19(1) (2023) - [j29]Davide Chicco, Fabio Cumbo, Claudio Angione:
Ten quick tips for avoiding pitfalls in multi-omics data integration analyses. PLoS Comput. Biol. 19(7) (2023) - [j28]Davide Chicco, Umberto Ferraro Petrillo, Giuseppe Cattaneo:
Ten quick tips for bioinformatics analyses using an Apache Spark distributed computing environment. PLoS Comput. Biol. 19(7) (2023) - [j27]Davide Chicco, Simone Spolaor, Marco S. Nobile:
Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS Comput. Biol. 19(12) (2023) - 2022
- [j26]Davide Chicco, Abbas Alameer, Sara Rahmati, Giuseppe Jurman:
Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning. BioData Min. 15(1) (2022) - [j25]Abbas Alameer, Davide Chicco:
geoCancerPrognosticDatasetsRetriever: a bioinformatics tool to easily identify cancer prognostic datasets on Gene Expression Omnibus (GEO). Bioinform. 38(6): 1761-1763 (2022) - [j24]Davide Chicco, Gabriel Cerono, Davide Cangelosi:
A Survey on Publicly Available Open Datasets Derived From Electronic Health Records (EHRs) of Patients with Neuroblastoma. Data Sci. J. 21: 17 (2022) - [j23]Davide Chicco, Giuseppe Jurman:
A brief survey of tools for genomic regions enrichment analysis. Frontiers Bioinform. 2 (2022) - [j22]Davide Chicco, Giuseppe Jurman:
The ABC recommendations for validation of supervised machine learning results in biomedical sciences. Frontiers Big Data 5 (2022) - [j21]Davide Chicco, Giuseppe Jurman:
An Invitation to Greater Use of Matthews Correlation Coefficient in Robotics and Artificial Intelligence. Frontiers Robotics AI 9: 876814 (2022) - [j20]Davide Chicco, Giuseppe Agapito:
Nine quick tips for pathway enrichment analysis. PLoS Comput. Biol. 18(8) (2022) - [j19]Davide Chicco, Philip E. Bourne:
Ten simple rules for organizing a special session at a scientific conference. PLoS Comput. Biol. 18(8) (2022) - [j18]Davide Chicco, Luca Oneto, Erica Tavazzi:
Eleven quick tips for data cleaning and feature engineering. PLoS Comput. Biol. 18(12): 1010718 (2022) - 2021
- [j17]Davide Chicco, Giuseppe Jurman:
An Ensemble Learning Approach for Enhanced Classification of Patients With Hepatitis and Cirrhosis. IEEE Access 9: 24485-24498 (2021) - [j16]Davide Chicco, Valery Starovoitov, Giuseppe Jurman:
The Benefits of the Matthews Correlation Coefficient (MCC) Over the Diagnostic Odds Ratio (DOR) in Binary Classification Assessment. IEEE Access 9: 47112-47124 (2021) - [j15]Davide Chicco, Matthijs J. Warrens, Giuseppe Jurman:
The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment. IEEE Access 9: 78368-78381 (2021) - [j14]Davide Chicco, Giuseppe Jurman:
Arterial Disease Computational Prediction and Health Record Feature Ranking Among Patients Diagnosed With Inflammatory Bowel Disease. IEEE Access 9: 78648-78657 (2021) - [j13]Davide Chicco, Christopher A. Lovejoy, Luca Oneto:
A Machine Learning Analysis of Health Records of Patients With Chronic Kidney Disease at Risk of Cardiovascular Disease. IEEE Access 9: 165132-165144 (2021) - [j12]Davide Chicco, Luca Oneto:
Data analytics and clinical feature ranking of medical records of patients with sepsis. BioData Min. 14(1): 12 (2021) - [j11]Davide Chicco, Niklas Tötsch, Giuseppe Jurman:
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation. BioData Min. 14(1): 13 (2021) - [j10]Davide Chicco, Luca Oneto:
Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma. Health Informatics J. 27(1): 146045822098420 (2021) - [j9]Davide Chicco, Matthijs J. Warrens, Giuseppe Jurman:
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Comput. Sci. 7: e623 (2021) - [j8]Davide Chicco, Luca Oneto:
An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2759-2765 (2021) - 2020
- [j7]Davide Chicco, Giuseppe Jurman:
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC Medical Informatics Decis. Mak. 20(1): 16 (2020) - 2018
- [j6]Kelwin Fernandes, Davide Chicco, Jaime S. Cardoso, Jessica Fernandes:
Supervised deep learning embeddings for the prediction of cervical cancer diagnosis. PeerJ Comput. Sci. 4: e154 (2018) - [j5]Davide Chicco, Fernando Palluzzi, Marco Masseroli:
Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 954-965 (2018) - 2017
- [j4]Davide Chicco:
Ten quick tips for machine learning in computational biology. BioData Min. 10(1): 35:1-35:17 (2017) - 2016
- [j3]Davide Chicco, Marco Masseroli:
Ontology-Based Prediction and Prioritization of Gene Functional Annotations. IEEE ACM Trans. Comput. Biol. Bioinform. 13(2): 248-260 (2016) - 2015
- [j2]Pietro Pinoli, Davide Chicco, Marco Masseroli:
Computational algorithms to predict Gene Ontology annotations. BMC Bioinform. 16(S-6): S4 (2015) - [j1]Davide Chicco, Marco Masseroli:
Software Suite for Gene and Protein Annotation Prediction and Similarity Search. IEEE ACM Trans. Comput. Biol. Bioinform. 12(4): 837-843 (2015)
Conference and Workshop Papers
- 2023
- [c12]Patrizia Ribino, Claudia Di Napoli, Giovanni Paragliola, Luca Serino, Francesca Gasparini, Davide Chicco:
Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques. AIxAS@AI*IA 2023: 67-87 - 2015
- [c11]Davide Chicco, Marco Masseroli:
Validation Pipeline for Computational Prediction of Genomics Annotations. CIBB 2015: 233-244 - 2014
- [c10]Davide Chicco, Peter J. Sadowski, Pierre Baldi:
Deep autoencoder neural networks for gene ontology annotation predictions. BCB 2014: 533-540 - [c9]Davide Chicco, Eleonora Ciceri, Marco Masseroli:
Extended Spearman and Kendall Coefficients for Gene Annotation List Correlation. CIBB 2014: 19-32 - [c8]Pietro Pinoli, Davide Chicco, Marco Masseroli:
Latent Dirichlet Allocation based on Gibbs Sampling for gene function prediction. CIBCB 2014: 1-8 - 2013
- [c7]Davide Chicco, Marco Masseroli:
A discrete optimization approach for SVD best truncation choice based on ROC curves. BIBE 2013: 1-4 - [c6]Pietro Pinoli, Davide Chicco, Marco Masseroli:
Enhanced probabilistic latent semantic analysis with weighting schemes to predict genomic annotations. BIBE 2013: 1-4 - [c5]Pietro Pinoli, Davide Chicco, Marco Masseroli:
Weighting Scheme Methods for Enhanced Genomic Annotation Prediction. CIBB 2013: 76-89 - 2012
- [c4]Marco Masseroli, Davide Chicco, Pietro Pinoli:
Probabilistic Latent Semantic Analysis for prediction of Gene Ontology annotations. IJCNN 2012: 1-8 - 2011
- [c3]Davide Chicco, Marco Tagliasacchi, Marco Masseroli:
Genomic Annotation Prediction Based on Integrated Information. CIBB 2011: 238-252 - [c2]Marco Masseroli, Marco Tagliasacchi, Davide Chicco:
Semantically improved genome-wide prediction of Gene Ontology annotations. ISDA 2011: 1080-1085 - 2010
- [c1]Davide Chicco, Marina Resta:
An intraday trading model based on Artificial Immune Systems. WIRN 2010: 62-68
Parts in Books or Collections
- 2021
- [p1]Davide Chicco:
Siamese Neural Networks: An Overview. Artificial Neural Networks, 3rd Edition 2021: 73-94
Editorship
- 2022
- [e1]Davide Chicco, Angelo M. Facchiano, Erica Tavazzi, Enrico Longato, Martina Vettoretti, Anna Bernasconi, Simone Avesani, Paolo Cazzaniga:
Computational Intelligence Methods for Bioinformatics and Biostatistics - 17th International Meeting, CIBB 2021, Virtual Event, November 15-17, 2021, Revised Selected Papers. Lecture Notes in Computer Science 13483, Springer 2022, ISBN 978-3-031-20836-2 [contents]
Reference Works
- 2019
- [r1]Davide Chicco, Marco Masseroli:
Biological and Medical Ontologies: Protein Ontology (PRO). Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 832-837
Informal and Other Publications
- 2020
- [i1]Chang Cao, Davide Chicco, Michael M. Hoffman:
The MCC-F1 curve: a performance evaluation technique for binary classification. CoRR abs/2006.11278 (2020)
Coauthor Index
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