J
Jobie Budd
Researcher at London Centre for Nanotechnology
Publications - 8
Citations - 913
Jobie Budd is an academic researcher from London Centre for Nanotechnology. The author has contributed to research in topics: Engineering & Computer science. The author has an hindex of 2, co-authored 4 publications receiving 374 citations. Previous affiliations of Jobie Budd include University College London.
Papers
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Journal ArticleDOI
Digital technologies in the public-health response to COVID-19.
Jobie Budd,Jobie Budd,Benjamin S. Miller,Erin M. Manning,Vasileios Lampos,Mengdie Zhuang,Michael Edelstein,Geraint Rees,Vincent C. Emery,Molly M. Stevens,Neil Keegan,Michael J. Short,Deenan Pillay,Ed Manley,Ingemar J. Cox,Ingemar J. Cox,David L Heymann,Anne M Johnson,Rachel A. McKendry,Rachel A. McKendry +19 more
TL;DR: The future of public health is likely to become increasingly digital, and the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases is reviewed.
Journal ArticleDOI
Taking connected mobile-health diagnostics of infectious diseases to the field
Christopher S. Wood,Michael R. Thomas,Jobie Budd,Tivani P. Mashamba-Thompson,Kobus Herbst,Deenan Pillay,Rosanna W. Peeling,Anne M Johnson,Rachel A. McKendry,Molly M. Stevens +9 more
TL;DR: Combining mobile phone technologies with infectious disease diagnostics can increase patients’ access to testing and treatment and provide public health authorities with new ways to monitor and control outbreaks of infectious diseases.
Journal ArticleDOI
Deep learning of HIV field-based rapid tests.
Valérian Turbé,Carina Herbst,Thobeka Mngomezulu,Sepehr Meshkinfamfard,Nondumiso Dlamini,Thembani Mhlongo,Theresa Smit,Valeriia Cherepanova,Koki Shimada,Jobie Budd,Jobie Budd,Nestor Arsenov,Steven G. Gray,Deenan Pillay,Kobus Herbst,Maryam Shahmanesh,Rachel A. McKendry,Rachel A. McKendry +17 more
TL;DR: In this article, the authors used deep learning to classify images of rapid human immunodeficiency virus (HIV) tests acquired in rural South Africa using newly developed image capture protocols with the Samsung SM-P585 tablet.
Journal ArticleDOI
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Harry Coppock,George W. Nicholson,Ivan Kiskin,Vasiliki Koutra,Kieran Baker,Jobie Budd,Richard Payne,Emma Karoune,David Hurley,Alexander Titcomb,Sabrina Egglestone,Ana Tendero Cañadas,L Butler,Radka Jersakova,Jonathon Mellor,Selina Patel,Tracey Thornley,P. H. Diggle,Sylvia Lorena Richardson,Josef Packham,Björn Schuller,Davide Pigoli,Steven G. Gilmour,Stephen J. Roberts,C. Holmes +24 more
TL;DR: In this article , audio-based deep learning classifiers were used to predict severe acute respiratory syndrome coronavirus 2 (SARSCoV2) infection status in 67,842 individuals.
Journal ArticleDOI
Lateral flow test engineering and lessons learned from COVID-19
Jobie Budd,Benjamin S. Miller,Nicole E. Weckman,Dounia Cherkaoui,Da Huang,Alyssa T. DeCruz,Noah Fongwen,Gyeo-Re Han,Marta Broto,Claudia Estcourt,Jo Gibbs,Deenan Pillay,Pam Sonnenberg,Robyn Meurant,Michael R. Thomas,Neil Keegan,Molly M. Stevens,Eleni Nastouli,Eric J. Topol,Anne M Johnson,Maryam Shahmanesh,Aydogan Ozcan,J. J. Collins,Marta Fernandez Suarez,Bill Rodriguez,Rosanna W. Peeling,Rachel A. McKendry +26 more
TL;DR: The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic as mentioned in this paper .