Davide Chicco

Scopus Author ID ResearcherID Loop profile ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 47

Top Venues

PLoS computational biology

BioData mining

Methods in molecular biology (Clifton, N.J.)

Journal of healthcare informatics research

Krembil Research Institute

Politecnico di Milano (PHD)

This page only lists publications with an associated author ORCID identifier.

Affiliation History

Krembil Research Institute

Canada

scientific associate researcher :: University Health Network

Peter Munk Cardiac Centre Sep 24 2018

Canada

Scientific associate researcher :: University Health Network

Princess Margaret Cancer Centre Sep 07 2014 - Sep 08 2018

Canada

Postdoctoral researcher :: University Health Network

Education History

Politecnico di Milano

Italy

PHD :: Dipartimento di Elettronica Informazione e Bioingegneria (DEIB)

University of Genoa

Italy

MSC :: Department of Computer Science (DIBRIS)

University of Genoa

Italy

BSC :: Department of Computer Science (DIBRIS)

Publications

Maximiliano Mollura, Davide Chicco, Alessia Paglialonga, Riccardo Barbieri
Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records. PLOS digital health 3 (3) (2024)
Maximiliano Mollura, Davide Chicco, Alessia Paglialonga, Riccardo Barbieri
Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records. PLOS digital health 3 (3) (2024)
Davide Chicco, Giuseppe Jurman
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData mining 16 (1) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Tiziana Sanavia, Giuseppe Jurman
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. BioData mining 16 (1) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Fabio Cumbo, Claudio Angione
Ten quick tips for avoiding pitfalls in multi-omics data integration analyses. PLoS computational biology 19 (7) (2023)
Davide Chicco, Simone Spolaor, Marco Salvatore Nobile
Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS computational biology 19 (12) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Simone Spolaor, Marco Salvatore Nobile
Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS computational biology 19 (12) (2023)
Davide Chicco, Giuseppe Jurman
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData mining 16 (1) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Rakesh Shiradkar
Ten quick tips for computational analysis of medical images. PLoS computational biology 19 (1) (2023)
Davide Chicco, Simone Spolaor, Marco Salvatore Nobile
Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS computational biology 19 (12) (2023)
Davide Chicco, Giuseppe Jurman
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData mining 16 (1) (2023)
Davide Chicco, Tiziana Sanavia, Giuseppe Jurman
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. BioData mining 16 (1) (2023)
Gabriel Cerono, Ombretta Melaiu, Davide Chicco
Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme. Journal of healthcare informatics research 8 (1) (2023)
Davide Chicco, Tiziana Sanavia, Giuseppe Jurman
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. BioData mining 16 (1) (2023)
Davide Chicco, Giuseppe Jurman
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData mining 16 (1) (2023)
Davide Chicco, Giuseppe Jurman
Ten simple rules for providing bioinformatics support within a hospital. BioData mining 16 (1) (2023)
Davide Chicco, Giuseppe Jurman
Ten simple rules for providing bioinformatics support within a hospital. BioData mining 16 (1) (2023)
Davide Chicco, Simone Spolaor, Marco Salvatore Nobile
Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS computational biology 19 (12) (2023)
Gabriel Cerono, Ombretta Melaiu, Davide Chicco
Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme. Journal of healthcare informatics research 8 (1) (2023)
Davide Chicco, Umberto Ferraro Petrillo, Giuseppe Cattaneo
Ten quick tips for bioinformatics analyses using an Apache Spark distributed computing environment. PLoS computational biology 19 (7) (2023)
Davide Chicco, Luca Oneto, Erica Tavazzi
Eleven quick tips for data cleaning and feature engineering. PLoS computational biology 18 (12) (2022)
Davide Chicco, Luca Oneto, Erica Tavazzi
Eleven quick tips for data cleaning and feature engineering. PLoS computational biology 18 (12) (2022)
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 mining 15 (1) (2022)
Davide Chicco, Luca Oneto, Erica Tavazzi
Eleven quick tips for data cleaning and feature engineering. PLoS computational biology 18 (12) (2022)
Davide Chicco, Luca Oneto, Erica Tavazzi
Eleven quick tips for data cleaning and feature engineering. PLoS computational biology 18 (12) (2022)
Davide Chicco
geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO). Methods in molecular biology (Clifton, N.J.) 2401 (2022)
Davide Chicco, Luca Oneto, Erica Tavazzi
Eleven quick tips for data cleaning and feature engineering. PLoS computational biology 18 (12) (2022)
Davide Chicco, Giuseppe Agapito
Nine quick tips for pathway enrichment analysis. PLoS computational biology 18 (8) (2022)
Davide Chicco, Philip E Bourne
Ten simple rules for organizing a special session at a scientific conference. PLoS computational biology 18 (8) (2022)
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 journal 27 (1) (2021)
Davide Chicco
Siamese Neural Networks: An Overview. Methods in molecular biology (Clifton, N.J.) 2190 (2021)
Davide Chicco, Trent Faultless
Brief Survey on Machine Learning in Epistasis. Methods in molecular biology (Clifton, N.J.) 2212 (2021)
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 mining 14 (1) (2021)
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. Computer science 7 (2021)
Abbas Alameer, Davide Chicco
geoCancerPrognosticDatasetsRetriever, a bioinformatics tool to easily identify cancer prognostic datasets on Gene Expression Omnibus (GEO). Bioinformatics (Oxford, England) (2021)
Davide Chicco, Giuseppe Jurman
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC medical informatics and decision making 20 (1) (2020)
Davide Chicco, Giuseppe Jurman
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC genomics 21 (1) (2020)
Davide Chicco, Giuseppe Jurman
Survival prediction of patients with sepsis from age, sex, and septic episode number alone. Scientific reports 10 (1) (2020)
Sheojung Shin, Peter C Austin, Heather Joan Ross, Husam Abdel-Qadir, Cassandra Freitas, George Tomlinson, Davide Chicco, Meera Mahendiran, Patrick R Lawler, Filio Billia, Anthony O Gramolini, Slava Epelman, Bo Wang, Douglas S Lee
Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality. ESC heart failure 8 (1) (2020)
Davide Chicco, Cristina Rovelli
Computational prediction of diagnosis and feature selection on mesothelioma patient health records. PloS one 14 (1) (2019)
Kelwin Fernandes, Davide Chicco, Jaime S Cardoso, Jessica Fernandes
Supervised deep learning embeddings for the prediction of cervical cancer diagnosis. PeerJ. Computer science 4 (2018)
Davide Chicco
Ten quick tips for machine learning in computational biology. BioData mining 10 (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Davide Chicco