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María-Inés Acosta-Urigüen

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Journal Articles

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2024
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  - journals/iswa/LimaAO24
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  - https://dblp.org/rec/journals/iswa/LimaAO24
Juan-Fernando Lima, María-Inés Acosta-Urigüen, Marcos Orellana:
Machine learning and knowledge engineering for cognitive memory assessment of age groups by anomalies in a serious game. Intell. Syst. Appl. 21: 200301 (2024)

Conference and Workshop Papers

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2024
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  - conf/ict4ageingwell/Acosta-UriguenH24
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María-Inés Acosta-Urigüen, Juan Pablo Holguin, Mateo Sebastián Zea-Paredes, Juan-Fernando Lima, Alexandra Bermeo, Javier Díaz, Ivana Harari:
Conceptualizing the Active Ageing Index (AAI): A Systematic Literature Review of Frameworks and Supporting Digital Tools. ICT4AWE 2024: 276-283
2022
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  - conf/ict4ageingwell/LimaCAOB22
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Juan-Fernando Lima, Priscila Cedillo, María-Inés Acosta-Urigüen, Marcos Orellana, Alexandra Bueno-Pacheco:
Rescuing Relevant Features from Active Aging Surveys: A Data Mining Perspective. ICT4AWE (Revised Selected Papers) 2022: 138-156
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María-Inés Acosta-Urigüen, Marcos Orellana, Priscila Cedillo:
Data Mining Techniques for Analysing Data Extracted from Serious Games: A Systematic Literature Review. ICT4AWE 2022: 220-227
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  - conf/ict4ageingwell/SarangoPASCO22
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Angel Alberto Jiménez Sarango, Andrés Patiño, María-Inés Acosta-Urigüen, Juan Gabriel Flores Sanchez, Priscila Cedillo, Marcos Orellana:
Analysis of Psychological Test Data by using K-means Method. ICT4AWE 2022: 236-243
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María-Inés Acosta-Urigüen, Priscila Cedillo, Marcos Orellana, Alexandra Bueno, Juan-Fernando Lima, Daniela Prado:
Finding Insights between Active Aging Variables: Towards a Data Mining Approach. ICT4AWE 2022: 268-275

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