Machine learning applications in risk management: Trends and research agenda DOI Creative Commons
Alejandro Valencia-Arías, Jesús Alberto Jiménez García, Erica Agudelo-Ceballos

et al.

F1000Research, Journal Year: 2025, Volume and Issue: 14, P. 233 - 233

Published: April 7, 2025

Abstract Risk management has become a foundational aspect in numerous industries, propelling the implementation of machine learning technologies for impact assessment, prevention, and decision-making processes. Nevertheless, lacunae extant literature persist, particularly with regard to identification emergent trends transversal applications. This study addresses this limitation through bibliometric analysis scientific production Scopus Web Science, adhering PRISMA-2020 declaration. The findings reveal substantial growth publications on applied risk management, an increase 98.99% between 2018 2023. China, South Korea, United States are identified as primary research-producing countries. also identifies emerging trends, such application evaluation urban trees risks associated pandemic severe acute respiratory syndrome (SARS-CoV-2). Key terms include random forest, support vector machines (SVM), credit while prediction, postpartum depression, big data, security emerge new areas study. Furthermore, there is transition from traditional approaches stacking advanced deep feature selection techniques, reflecting evolution discipline.

Language: Английский

Machine learning applications in risk management: Trends and research agenda DOI Creative Commons
Alejandro Valencia-Arías, Jesús Alberto Jiménez García, Erica Agudelo-Ceballos

et al.

F1000Research, Journal Year: 2025, Volume and Issue: 14, P. 233 - 233

Published: April 7, 2025

Abstract Risk management has become a foundational aspect in numerous industries, propelling the implementation of machine learning technologies for impact assessment, prevention, and decision-making processes. Nevertheless, lacunae extant literature persist, particularly with regard to identification emergent trends transversal applications. This study addresses this limitation through bibliometric analysis scientific production Scopus Web Science, adhering PRISMA-2020 declaration. The findings reveal substantial growth publications on applied risk management, an increase 98.99% between 2018 2023. China, South Korea, United States are identified as primary research-producing countries. also identifies emerging trends, such application evaluation urban trees risks associated pandemic severe acute respiratory syndrome (SARS-CoV-2). Key terms include random forest, support vector machines (SVM), credit while prediction, postpartum depression, big data, security emerge new areas study. Furthermore, there is transition from traditional approaches stacking advanced deep feature selection techniques, reflecting evolution discipline.

Language: Английский

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