Clinical applications of machine learning algorithms: Beyond the black box DS Watson, J Krutzinna, IN Bruce, CE Griffiths, IB McInnes, MR Barnes, ... The BMJ 364, 2019 | 373 | 2019 |
Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes M Lewis, M Barnes, K Blighe, K Goldmann, S Rana, J Hackney, ... Cell Reports 28 (9), 2019 | 289 | 2019 |
The rhetoric and reality of anthropomorphism in artificial intelligence D Watson Minds & Machines 29 (3), 414-440, 2019 | 145 | 2019 |
Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci HL Nicholls, CR John, DS Watson, PB Munroe, MR Barnes, CP Cabrera Frontiers in Genetics 11, 350, 2020 | 138 | 2020 |
M3C: Monte Carlo reference-based consensus clustering CR John, D Watson, D Russ, K Goldmann, M Ehrenstein, C Pitzalis, ... Scientific reports 10 (1), 1816, 2020 | 113 | 2020 |
Signatures of inflammation and impending multiple organ dysfunction in the hyperacute phase of trauma: A prospective cohort study CP Cabrera, J Manson, JM Shepherd, HD Torrance, D Watson, ... PLoS medicine 14 (7), e1002352, 2017 | 108 | 2017 |
Are the dead taking over Facebook? A Big Data approach to the future of death online CJ Ohman, D Watson Big Data & Society, 2019 | 97 | 2019 |
The Explanation Game: A Formal Framework for Interpretable Machine Learning D Watson, L Floridi Synthese 198 (10), 9211-9242, 2020 | 86 | 2020 |
Spectrum: Fast density-aware spectral clustering for single and multi-omic data C John, D Watson, M Barnes, C Pitzalis, M Lewis Bioinformatics, 2019 | 86 | 2019 |
Sex differences in the nitrate-nitrite-NO• pathway: Role of oral nitrate-reducing bacteria V Kapil, KS Rathod, RS Khambata, M Bahra, S Velmurugan, A Purba, ... Free Radical Biology and Medicine 126, 113-121, 2018 | 83 | 2018 |
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice D Watson, L Gultchin, A Taly, L Floridi Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, 2021 | 64 | 2021 |
Crowdsourced science: sociotechnical epistemology in the e-research paradigm D Watson, L Floridi Synthese 195 (2), 741–764, 2016 | 64 | 2016 |
The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other? J Mökander, P Juneja, DS Watson, L Floridi Minds and Machines 32 (4), 751-758, 2022 | 62 | 2022 |
Conceptual challenges for interpretable machine learning D Watson Synthese 200, 1-33, 2022 | 55 | 2022 |
Testing conditional independence in supervised learning algorithms D Watson, M Wright Machine Learning 110, 2107–2129, 2021 | 43 | 2021 |
A Framework for Multi-Omic Prediction of Treatment Response to Biologic Therapy for Psoriasis AC Foulkes, DS Watson, DF Carr, JG Kenny, T Slidel, R Parslew, ... Journal of Investigative Dermatology 139 (1), 100-107, 2019 | 39 | 2019 |
Interpretable machine learning for genomics D Watson Human Genetics, 2021 | 36 | 2021 |
Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming FAH Cooles, J Tarn, DW Lendrem, N Naamane, CMA Lin, B Millar, ... Annals of the rheumatic diseases 81 (9), 1214-1223, 2022 | 28 | 2022 |
Research techniques made simple: bioinformatics for genome-scale biology AC Foulkes, DS Watson, CEM Griffiths, RB Warren, W Huber, MR Barnes Journal of Investigative Dermatology 137 (9), e163-e168, 2017 | 23 | 2017 |
The RA-MAP Consortium: a working model for academia–industry collaboration AP Cope, MR Barnes, A Belson, M Binks, S Brockbank, ... Nature Reviews Rheumatology 14 (1), 53, 2018 | 21 | 2018 |