Anna Palczewska
Anna Palczewska
Verified email at leedsbeckett.ac.uk
Title
Cited by
Cited by
Year
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
712014
Data governance in predictive toxicology: A review
X Fu, A Wojak, D Neagu, M Ridley, K Travis
Journal of cheminformatics 3 (1), 24, 2011
522011
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
452013
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
292017
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
202016
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
162013
Using Pareto points for model identification in predictive toxicology
A Palczewska, D Neagu, M Ridley
Journal of cheminformatics 5 (1), 16, 2013
42013
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
22019
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
22017
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
12019
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
12015
Assocation rule learning
A Palczewska
12012
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
12011
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
2019
Advances in Drug Toxicology
U Gundert‑Remy, J Sachs, F Bévalot, IM McIntyre, A Palczewska, ...
Advances in Drug Toxicology, 341, 2016
2016
Interpretation, Identification and Reuse of Models. Theory and algorithms with applications in predictive toxicology.
AM Palczewska
University of Bradford, 2015
2015
The political economy of ageing and later life: critical perspectives by Alan Walker and Liam Foster [Book review]
C Powell
2015
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
2015
Using computational methods for the prediction of drug vehicles
P Mistry, A Palczewska, D Neagu, P Trundle
2014 14th UK Workshop on Computational Intelligence (UKCI), 1-7, 2014
2014
Paper Title Author (s) Page No Preface iii Committee iv Biographies vi
C Akkaya, M Jakob, H Krcmar, GP Dias, S Doski, M Jneid, I Saleh, ...
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Articles 1–20