David S. Watson

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Michael R BarnesProfessor of Bioinformatics, Centre for Translational Bioinformatics, QMULqmul.ac.uk의 이메일 확인됨
Luciano FloridiYale University - Alma Mater Studiorum University of Bolognayale.edu의 이메일 확인됨
Christopher E.M. GriffithsProfessor of Dermatology, University of Manchestermanchester.ac.uk의 이메일 확인됨
Jakob MökanderUniversity of Oxfordoii.ox.ac.uk의 이메일 확인됨
Jenny KrutzinnaSenior Researcher, Department of Media and Communication, University of Oslomedia.uio.no의 이메일 확인됨
Carl ÖhmanUppsala Universitystatsvet.uu.se의 이메일 확인됨
Marvin N. WrightLeibniz Institute for Prevention Research and Epidemiology – BIPS & University of Bremenleibniz-bips.de의 이메일 확인됨
Claudia P CabreraQueen Mary Universityqmul.ac.uk의 이메일 확인됨
Ricardo SilvaProfessor of Statistical Machine Learning and Data Science, Department of Statistical Science, UCLstats.ucl.ac.uk의 이메일 확인됨
Myles LewisProfessor of Rheumatology, Queen Mary University of Londonqmul.ac.uk의 이메일 확인됨
Costantino PitzalisProfessor of Experimental Medicine and Rheumatology QMULqmul.ac.uk의 이메일 확인됨
Sandra NgQueen Mary University of Londonqmul.ac.uk의 이메일 확인됨
Christopher R JohnQMULqmul.ac.uk의 이메일 확인됨
Amy FoulkesUniversity of Manchestermanchester.ac.uk의 이메일 확인됨
Ian BruceProfessor of Rheumatology, University of Manchestermanchester.ac.uk의 이메일 확인됨
Kristin BleschPhD Student, University of Bremenuni-bremen.de의 이메일 확인됨
Michael EhrensteinUCLucl.ac.uk의 이메일 확인됨
Katriona GoldmannResearch Data Scientist, the Alan Turing Instituteturing.ac.uk의 이메일 확인됨
Karim BrohiProfessor of Trauma Sciences, Queen Mary University of Londonqmul.ac.uk의 이메일 확인됨
Hew D TorranceNIHR Clinical Lecturer | SpR in Anaesthetics & Intensive Care Medicine, Imperial Collegeimperial.ac.uk의 이메일 확인됨

팔로우

David S. Watson

Lecturer in Artificial Intelligence, King's College London

kcl.ac.uk의 이메일 확인됨 - 홈페이지

Machine Learning Philosophy of Science Epistemology Bioinformatics AI Ethics


제목 서지정보순 정렬 연도순 정렬 제목순 정렬	인용 인용	연도
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	426	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	338	2019
The rhetoric and reality of anthropomorphism in artificial intelligence D Watson Minds & Machines 29 (3), 414-440, 2019	181	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	155	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	133	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	117	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	115	2019
Spectrum: Fast density-aware spectral clustering for single and multi-omic data C John, D Watson, M Barnes, C Pitzalis, M Lewis Bioinformatics, 2019	102	2019
The Explanation Game: A Formal Framework for Interpretable Machine Learning D Watson, L Floridi Synthese 198 (10), 9211-9242, 2020	99	2020
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	98	2022
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	91	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	86	2021
Conceptual challenges for interpretable machine learning D Watson Synthese 200, 1-33, 2022	80	2022
Crowdsourced science: sociotechnical epistemology in the e-research paradigm D Watson, L Floridi Synthese 195 (2), 741–764, 2016	69	2016
Testing conditional independence in supervised learning algorithms D Watson, M Wright Machine Learning 110, 2107–2129, 2021	61	2021
The benefits and pitfalls of machine learning for biomarker discovery S Ng, S Masarone, D Watson, M Barnes Cell and Tissue Research, 2023	49	2023
Interpretable machine learning for genomics D Watson Human Genetics, 2021	49	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	44	2019
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	37	2022
The epistemological foundations of data science: a critical analysis J Desai, D Watson, V Wang, M Taddeo, L Floridi Synthese 200 (469), 2022	36*	2022

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