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 | 83 | 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 | 59 | 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 | 49 | 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 | 39 | 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 | 23 | 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 | 18 | 2013 |
Using Pareto points for model identification in predictive toxicology A Palczewska, D Neagu, M Ridley Journal of cheminformatics 5 (1), 1-16, 2013 | 5 | 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 | 3 | 2019 |
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 | 3 | 2017 |
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 | 2 | 2020 |
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 | 2 | 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 | 1 | 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 | 1 | 2015 |
Assocation rule learning A Palczewska | 1 | 2012 |
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 | 1 | 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 | | 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 |