Comparing empirical ROC curves using a Java application: CERCUS

Detalhes bibliográficos
Autor(a) principal: Moreira, Daniel
Data de Publicação: 2019
Outros Autores: Braga, A. C.
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/1822/70507
Resumo: Receiver Operating Characteristic (ROC) analysis is a methodology that has gained much popularity in our days, especially in Medicine, since through the ROC curves, it provides a useful tool to evaluate and specify problems in the performance of a diagnostic indicator. The area under empirical ROC curve (AUC) it’s an indicator that can be used to compare two or more ROC curves. This work arose from the necessity of the existence of software that allows the calculation of the necessary measures to compare systems based on ROC curves. Several software, commercial and non-commercial, are available to perform the calculation of the measures associated to the ROC analysis. However, they present some flaws, especially when there is a need to compare independent samples with different dimensions, or also to compare two ROC curves that intersect. In this paper is presented a new application called CERCUS (Comparison of Empirical ROC Curves). This was developed using a programming language (Java) and stands out for the possibility of comparing two or more ROC curves that cross each other. The main objective of CERCUS is the calculation of several ROC estimates using different methods and make the ROC curves comparison, even if there is an intersection, either for independent or paired samples. It also allows the graph representation of the ROC curve in a unitary plan as well the graph of the area between curves in comparison. This paper presents the program’s versatility in data entry, test menus and visualization of graphs and results.
id RCAP_1e7ed6c15afdb61ffc2f257247fc1138
oai_identifier_str oai:repositorium.sdum.uminho.pt:1822/70507
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Comparing empirical ROC curves using a Java application: CERCUSROC curveCERCUSJavaRScience & TechnologyReceiver Operating Characteristic (ROC) analysis is a methodology that has gained much popularity in our days, especially in Medicine, since through the ROC curves, it provides a useful tool to evaluate and specify problems in the performance of a diagnostic indicator. The area under empirical ROC curve (AUC) it’s an indicator that can be used to compare two or more ROC curves. This work arose from the necessity of the existence of software that allows the calculation of the necessary measures to compare systems based on ROC curves. Several software, commercial and non-commercial, are available to perform the calculation of the measures associated to the ROC analysis. However, they present some flaws, especially when there is a need to compare independent samples with different dimensions, or also to compare two ROC curves that intersect. In this paper is presented a new application called CERCUS (Comparison of Empirical ROC Curves). This was developed using a programming language (Java) and stands out for the possibility of comparing two or more ROC curves that cross each other. The main objective of CERCUS is the calculation of several ROC estimates using different methods and make the ROC curves comparison, even if there is an intersection, either for independent or paired samples. It also allows the graph representation of the ROC curve in a unitary plan as well the graph of the area between curves in comparison. This paper presents the program’s versatility in data entry, test menus and visualization of graphs and results.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019SpringerUniversidade do MinhoMoreira, DanielBraga, A. C.20192019-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/70507engMoreira D., Braga A.C. (2019) Comparing Empirical ROC Curves Using a Java Application: CERCUS. In: Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science, vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_397830302430120302-974310.1007/978-3-030-24302-9_3info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T05:52:43Zoai:repositorium.sdum.uminho.pt:1822/70507Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:33:06.038071Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Comparing empirical ROC curves using a Java application: CERCUS
title Comparing empirical ROC curves using a Java application: CERCUS
spellingShingle Comparing empirical ROC curves using a Java application: CERCUS
Moreira, Daniel
ROC curve
CERCUS
Java
R
Science & Technology
title_short Comparing empirical ROC curves using a Java application: CERCUS
title_full Comparing empirical ROC curves using a Java application: CERCUS
title_fullStr Comparing empirical ROC curves using a Java application: CERCUS
title_full_unstemmed Comparing empirical ROC curves using a Java application: CERCUS
title_sort Comparing empirical ROC curves using a Java application: CERCUS
author Moreira, Daniel
author_facet Moreira, Daniel
Braga, A. C.
author_role author
author2 Braga, A. C.
author2_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Moreira, Daniel
Braga, A. C.
dc.subject.por.fl_str_mv ROC curve
CERCUS
Java
R
Science & Technology
topic ROC curve
CERCUS
Java
R
Science & Technology
description Receiver Operating Characteristic (ROC) analysis is a methodology that has gained much popularity in our days, especially in Medicine, since through the ROC curves, it provides a useful tool to evaluate and specify problems in the performance of a diagnostic indicator. The area under empirical ROC curve (AUC) it’s an indicator that can be used to compare two or more ROC curves. This work arose from the necessity of the existence of software that allows the calculation of the necessary measures to compare systems based on ROC curves. Several software, commercial and non-commercial, are available to perform the calculation of the measures associated to the ROC analysis. However, they present some flaws, especially when there is a need to compare independent samples with different dimensions, or also to compare two ROC curves that intersect. In this paper is presented a new application called CERCUS (Comparison of Empirical ROC Curves). This was developed using a programming language (Java) and stands out for the possibility of comparing two or more ROC curves that cross each other. The main objective of CERCUS is the calculation of several ROC estimates using different methods and make the ROC curves comparison, even if there is an intersection, either for independent or paired samples. It also allows the graph representation of the ROC curve in a unitary plan as well the graph of the area between curves in comparison. This paper presents the program’s versatility in data entry, test menus and visualization of graphs and results.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/70507
url http://hdl.handle.net/1822/70507
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Moreira D., Braga A.C. (2019) Comparing Empirical ROC Curves Using a Java Application: CERCUS. In: Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science, vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_3
9783030243012
0302-9743
10.1007/978-3-030-24302-9_3
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833595388414656512