Items where Author is "Palczewska, A"

Sawczuk, T and Palczewska, A and Jones, B and Palczewski, J (2024) A Bayesian Mixture Model approach to expected possession values in rugby league. PLOS ONE, 19 (11). pp. 1-15. ISSN 1932-6203 DOI: https://doi.org/10.1371/journal.pone.0308222

Adeyemo, VE and Palczewska, A and Jones, B and Weaving, D (2024) The use of match-based exact movement activities to classify elite rugby league players into positional groups. International Journal of Data Science and Analytics. pp. 1-14. ISSN 2364-415X DOI: https://doi.org/10.1007/s41060-024-00626-6

Adeyemo, VE and Palczewska, A and Jones, B and Weaving, D (2024) Identification of pattern mining algorithm for rugby league players positional groups separation based on movement patterns. PLOS ONE, 19 (5). pp. 1-20. ISSN 1932-6203 DOI: https://doi.org/10.1371/journal.pone.0301608

Singh, B and Gorbenko, A and Palczewska, A and Tawfik, H (2023) Application of Machine Learning Techniques to Predict Teenage Obesity Using Earlier Childhood Measurements from Millennium Cohort Study. In: ICCBDC 2023: 2023 7th International Conference on Cloud and Big Data Computing, 17 August 2023 - 19 August 2023, Manchester, UK. DOI: https://doi.org/10.1145/3616131.3616139

Dalton-Barron, N and Palczewska, A and Weaving, D and Rennie, G and Beggs, C and Roe, G and Jones, B (2022) Clustering of match running and performance indicators to assess between- and within-playing position similarity in professional rugby league. J Sports Sci. ISSN 1466-447X DOI: https://doi.org/10.1080/02640414.2022.2100781

Collins, N and White, R and Palczewska, A and Weaving, D and Dalton-Barron, N and Jones, B (2022) Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match-play. European Journal of Sport Science. ISSN 1746-1391 DOI: https://doi.org/10.1080/17461391.2022.2027527

White, R and Palczewska, A and Weaving, D and Collins, N and Jones, B (2022) Sequential movement pattern-mining (SMP) in field-based team-sport: A framework for quantifying spatiotemporal data and improve training specificity? Journal of Sports Sciences, 40 (2). pp. 164-174. ISSN 0264-0414 DOI: https://doi.org/10.1080/02640414.2021.1982484

Palczewska, A and Markowska-Kaczmar, U and Neagu, D (2021) Interpreting Neural Networks Prediction for a Single Instance via Random Forest Feature Contributions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2. pp. 140-153. ISSN 0302-9743 DOI: https://doi.org/10.1007/978-3-030-77964-1_12

Sawczuk, T and Palczewska, A and Jones, B (2021) Development of an expected possession value model to analyse team attacking performances in rugby league. PLoS One, 16 (11). ISSN 1932-6203 DOI: https://doi.org/10.1371/journal.pone.0259536

Dalton-Barron, N and Palczewska, A and McLaren, SJ and Rennie, G and Beggs, C and Jones, B and Roe, G (2020) A league-wide investigation into variability of rugby league match running from 322 Super League games. Science and Medicine in Football. ISSN 2473-3938 DOI: https://doi.org/10.1080/24733938.2020.1844907

Palczewska, A and Kovarich, S and Ciacci, A and Fioravanzo, E and Basan, A and Neagu, D (2019) Ranking strategies to support toxicity prediction: a case study on potential LXR binders. Computational Toxicology, 10. pp. 130-144. ISSN 2468-1113 DOI: https://doi.org/10.1016/j.comtox.2019.01.004

Cassano, A and Marchese Robinson, RL and Palczewska, A and Puzyn, T and Gajewicz, A and Tran, L and Manganelli, S and Cronin, MTD (2016) Comparing the CORAL and Random Forest approaches for modelling the in vitro cytotoxicity of silica nanomaterials. Alternatives to Laboratory Animals, 44 (6). pp. 533-556. ISSN 0261-1929 DOI: https://doi.org/10.1177/026119291604400603