Anna Palczewska
Anna Palczewska
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Cited by
Interpreting random forest classification models using a feature contribution method
A Palczewska, J Palczewski, RM Robinson, D Neagu
Integration of reusable systems, 193-218, 2014
Data governance in predictive toxicology: A review
X Fu, A Wojak, D Neagu, M Ridley, K Travis
Journal of cheminformatics 3 (1), 1-16, 2011
Interpreting random forest models using a feature contribution method
A Palczewska, J Palczewski, RM Robinson, D Neagu
2013 IEEE 14th International Conference on Information Reuse & Integration …, 2013
Comparison of the predictive performance and interpretability of random forest and linear models on benchmark data sets
RL Marchese Robinson, A Palczewska, J Palczewski, N Kidley
Journal of chemical information and modeling 57 (8), 1773-1792, 2017
Comparing the CORAL and Random Forest approaches for modelling the in vitro cytotoxicity of silica nanomaterials.
A Cassano, RL Marchese Robinson, A Palczewska, T Puzyn, A Gajewicz, ...
Altern Lab Anim 44 (6), 533-556, 2016
Towards model governance in predictive toxicology
A Palczewska, X Fu, P Trundle, L Yang, D Neagu, M Ridley, K Travis
International Journal of Information Management 33 (3), 567-582, 2013
Using Pareto points for model identification in predictive toxicology
A Palczewska, D Neagu, M Ridley
Journal of cheminformatics 5 (1), 1-16, 2013
Application of unsupervised learning in weight-loss categorisation for weight management programs
O Babajide, H Tawfik, A Palczewska, A Gorbenko, A Astrup, JA Martinez, ...
2019 10th International Conference on Dependable Systems, Services and …, 2019
A league-wide investigation into variability of rugby league match running from 322 Super League games
N Dalton-Barron, A Palczewska, SJ McLaren, G Rennie, C Beggs, G Roe, ...
Science and Medicine in Football, 1-9, 2020
RobustSPAM for inference from noisy longitudinal data and preservation of privacy
A Palczewska, J Palczewski, G Aivaliotis, L Kowalik
2017 16th IEEE international conference on machine learning and applications …, 2017
A Machine Learning Approach to Short-Term Body Weight Prediction in a Dietary Intervention Program
O Babajide, T Hissam, P Anna, G Anatoliy, A Astrup, JA Martinez, ...
International Conference on Computational Science, 441-455, 2020
Ranking strategies to support toxicity prediction: a case study on potential LXR binders
A Palczewska, S Kovarich, A Ciacci, E Fioravanzo, A Bassan, D Neagu
Computational Toxicology 10, 130-144, 2019
In silico chemistry-based workflows to facilitate ADMET prediction for cosmetics-related substances
AN Richarz, P Alov, SJ Enoch, S Kovarich, Y Lan, T Meinl, C Mellor, ...
Toxicology Letters 2 (238), S170, 2015
Assocation rule learning
A Palczewska
Double Min-Score (DMS) Algorithm for automated model selection in predictive toxicology
A Wojak, D Neagu, M Ridley
United Kingdom Workshop in Computational Intelligence (UKCI 2011) 150, 156, 2011
Public Services, Personal Data and Machine Learning: Prospects for Infrastructures and Ecosystems
J Keen, R Ruddle, J Palczewski, G Aivaliotis, M Adnan, A Palczewska, ...
ECDG 2019 19th European Conference on Digital Government, 51, 2019
Advances in Drug Toxicology
U Gundert‑Remy, J Sachs, F Bévalot, IM McIntyre, A Palczewska, ...
Advances in Drug Toxicology, 341, 2016
Interpretation, Identification and Reuse of Models. Theory and algorithms with applications in predictive toxicology.
AM Palczewska
University of Bradford, 2015
The political economy of ageing and later life: critical perspectives by Alan Walker and Liam Foster [Book review]
C Powell
Chemical and mechanistic similarity based assessment of the cosmetics space supporting the evaluation of cosmetics-related substances
AN Richarz, SJ Enoch, E Fioravanzo, S Kovarich, JC Madden, C Mellor, ...
Toxicology Letters 2 (238), S170, 2015
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