TY - JOUR
T1 - Methodology for the Use of Machine Learning, Applied in Predicting the Level of Success in Legal Cases
AU - Auccahuasi, Wilver
AU - Herrera, Lucas
AU - Rojas Romero, Karin Corina
AU - Urbano, Kitty
AU - Peláez, Brayan
AU - Peña, Pedro Flores
AU - Osorio, Yuly Montes
AU - Bernardo, Grisi
AU - Bernardo Santiago Vda De Leon, Madelaine
AU - Meza, Sandra
AU - Ovalle, Christian
AU - Hilario, Francisco
AU - Liendo Arevalo, Milner David
AU - Sernaque, Fernando
N1 - Publisher Copyright:
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
PY - 2022
Y1 - 2022
N2 - ICTs have allowed the applications of artificial intelligence to grow exponentially, where different applications are being presented, based on the application of neural networks as prediction mechanisms for different processes and applications, in the present work the use of the Neural networks for the legal case prediction process, in which the analysis of approximately 200 cases was used between cases that had "positive and negative" final results, the expected results after implementing the solution in the MATLAB tool, they presented us effectiveness results in a value of 93%, as a conclusion we can indicate that the model provided allows us to be applied in other conditions as well as to be scaled, taking into account the historical data that may be available for the training process.
AB - ICTs have allowed the applications of artificial intelligence to grow exponentially, where different applications are being presented, based on the application of neural networks as prediction mechanisms for different processes and applications, in the present work the use of the Neural networks for the legal case prediction process, in which the analysis of approximately 200 cases was used between cases that had "positive and negative" final results, the expected results after implementing the solution in the MATLAB tool, they presented us effectiveness results in a value of 93%, as a conclusion we can indicate that the model provided allows us to be applied in other conditions as well as to be scaled, taking into account the historical data that may be available for the training process.
KW - Artificial Intelligence
KW - cases
KW - legal
KW - methodology
KW - protocol
UR - http://www.scopus.com/inward/record.url?scp=85132278300&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85132278300
SN - 1613-0073
VL - 3146
SP - 48
EP - 54
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 2022 Workshop on Artificial Intelligence, WAI 2022
Y2 - 28 January 2022 through 29 January 2022
ER -