VU Medicinos fakulteto autoriaus 'Dalia Breskuvienė' publikacijų sąrašas

2025
1 Breskuvienė, Dalia (tyrėjas). Klasteriais pritaikyta mokymo strategija kredito kortelių sukčiavimo aptikimui = Cluster-specific training strategy for credit card fraud detection. Vilnius, 2025. 1 failas. DOI: 10.18279/MIDAS.259980.
2 Breskuvienė, Dalia (tyrėjas). Kategorinių požymių kodavimo metodai klasifikatorių veikimo gerinimui, taikant juos nesubalansuotiems sukčiavimo operacijų duomenims. = Categorical feature encoding techniques for improved classifier performance when dealing with imbalanced data of fraudulent transactions. Vilnius, 2025. 1 failas. DOI: 10.18279/MIDAS.261073.
3 Breskuvienė, Dalia (tyrėjas). Kredito kortelių sukčiavimo aptikimo gerinimas: labai nesubalansuotų duomenų atvejis = Enhancing credit card fraud detection: highly imbalanced data case. Vilnius, 2025. 5 failai. DOI: 10.18279/MIDAS.261094.

2024
1 Maselienė, Tatjana; Žukienė, Guoda; Laurinavičienė, Anna; Breskuvienė, Dalia; Ramašauskaitė, Diana; Dženkevičiūtė, Vilma. Alterations in maternal cardiovascular parameters and their impact on uterine and fetal circulation in hypertensive pregnancies and fetal growth restriction // International journal of cardiology cardiovascular risk and prevention. Amsterdam : Elsevier. ISSN 2772-4875. 2024, vol. 22, art. no. 200316, p. [1-6]. DOI: 10.1016/j.ijcrp.2024.200316. [DB: Emerging Sources Citation Index (Web of Science), Scopus]
2 Breskuvienė, Dalia; Dzemyda, Gintautas. Highly imbalanced data case: pattern-guided feature selection to detect financial fraud // DAMSS: 15th conference on data analysis methods for software systems, Druskininkai, Lithuania, November 28-30, 2024. Vilnius : Vilniaus universiteto leidykla, 2024. eISBN 9786090711125. p. 12-13. (Vilnius University Proceedings, eISSN 2669-0233 ; vol. 52). DOI: 10.15388/DAMSS.15.2024. [DB: Dimensions]
3 Breskuvienė, Dalia; Dzemyda, Gintautas. Enhancing credit card fraud detection: highly imbalanced data case // Journal of big data. London : Springer Nature. eISSN 2196-1115. 2024, vol. 11, iss. 1, art. no. 182, p. [1-24]. DOI: 10.1186/s40537-024-01059-5. [DB: Science Citation Index Expanded (Web of Science), Scopus]

2023
1 Breskuvienė, Dalia; Dzemyda, Gintautas. Imbalanced data classification approach based on clustered training set // Data science in applications /editors: Dzemyda, G., Bernatavičienė, J., Kacprzyk, J. Cham : Springer, 2023. ISBN 9783031244520. eISBN 9783031244537. p. 43-62. (Studies in Computational Intelligence, ISSN 1860-949X, eISSN 1860-9503 ; vol. 1084). DOI: 10.1007/978-3-031-24453-7_3.
2 Breskuvienė, Dalia; Dzemyda, Gintautas. Categorical feature encoding techniques for improved classifier performance when dealing with imbalanced data of fraudulent transactions // International journal of computers communications & control. Oradea : Agora University. ISSN 1841-9836. eISSN 1841-9844. 2023, vol. 18, iss. 3, art. no. 5433, p. [1-17]. DOI: 10.15837/ijccc.2023.3.5433. [DB: Science Citation Index Expanded (Web of Science), Scopus] [IF: 2.000; AIF: 4.350; Q3 (2023 InCities JCR SCIE)]
3 Breskuvienė, Dalia; Dzemyda, Gintautas. What is a concept drift, and does it affect machine learning performance? // DAMSS: 14th conference on data analysis methods for software systems, Druskininkai, Lithuania, November 30 - December 2, 2023. Vilnius : Vilniaus universiteto leidykla, 2023. eISBN 9786090709856. p. 14. (Vilnius University Proceedings, eISSN 2669-0233 ; vol. 39). DOI: 10.15388/DAMSS.14.2023. [DB: Dimensions]

2022
1 Breskuvienė, Dalia; Dzemyda, Gintautas. Clustering-based optimization in fraud detection classifier training // EURO 2022: [32nd European Conference on Operational Research (EURO XXXII)], Espoo, Finland, July 3-6, 2022 : abstract book. Espoo : Aalto university, 2022. ISBN 9789519525419. p. 152. Prieiga per internetą: <https://www.euro-online.org/conf/admin/tmp/program-euro32.pdf>.
2 Breskuvienė, Dalia; Dzemyda, Gintautas. Autoencoder for fraudulent transactions data feature engineering // DAMSS: 13th conference on data analysis methods for software systems, Druskininkai, Lithuania, December 1–3, 2022. Vilnius : Vilniaus universiteto leidykla, 2022. ISBN 9786090707944. eISBN 9786090707951. p. 11. (Vilnius University Proceedings, eISSN 2669-0233 ; vol. 31). DOI: 10.15388/DAMSS.13.2022.

2021
1 Breskuvienė, Dalia. Forbearance prediction using XGBoost and LightGBM models // DAMSS 2021: 12th conference on data analysis methods for software systems, Druskininkai, Lithuania, December 2–4, 2021. Vilnius : Vilnius University Press, 2021. ISBN 9786090706732. eISBN 9786090706749. p. 7. (Vilnius University proceedings, eISSN 2669-0233 ; vol. 17). DOI: 10.15388/DAMSS.12.2021.