Articles with public access mandates - Laura SbaffiLearn more
Available somewhere: 9
Integrating FATE/critical data studies into data science curricula: where are we going and how do we get there?
J Bates, D Cameron, A Checco, P Clough, F Hopfgartner, S Mazumdar, ...
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
Mandates: European Commission
LMIC-PRIEST: Derivation and validation of a clinical severity score for acutely ill adults with suspected COVID-19 in a middle-income setting
C Marincowitz, P Hodkinson, D McAlpine, G Fuller, S Goodacre, PA Bath, ...
Plos one 18 (6), e0287091, 2023
Mandates: Bill & Melinda Gates Foundation, US National Institutes of Health, US Agency …
Using a 360 camera as a mobile data collection method towards understanding information types and use in running
LJ Pretlove, AM Cox, L Sbaffi, F Hopfgartner
Proceedings of the Association for Information Science and Technology 57 (1 …, 2020
Mandates: UK Arts & Humanities Research Council
Prognostic accuracy of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study
C Marincowitz, L Sbaffi, P Hodkinson, D McAlpine, G Fuller, S Goodacre, ...
medRxiv, 2022.08. 23.22279112, 2022
Mandates: National Institute for Health Research, UK, Health Data Research, UK
Addressing the information needs of informal carers in Malawi: a healthcare intervention based on co-creation
ED Zamani, L Sbaffi, K Kalua
Journal of Documentation 80 (1), 131-157, 2024
Mandates: UK Research & Innovation
Intersectional Analysis of the Challenges and Opportunities of Equitable Remote Operation in the UK Maritime Sector
A Cai, CM Bentley, E Zamani, M Naiseh, L Sbaffi
Proceedings of the First International Symposium on Trustworthy Autonomous …, 2023
Mandates: UK Research & Innovation
External validation of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study
C Marincowitz, L Sbaffi, M Hasan, P Hodkinson, D McAlpine, G Fuller, ...
Emergency Medicine Journal 40 (7), 509-517, 2023
Mandates: Bill & Melinda Gates Foundation, US National Institutes of Health, US Agency …
Training and testing of a gradient boosted machine learning model to predict adverse outcome in patients presenting to emergency departments with suspected covid-19 infection …
GW Fuller, M Hasan, P Hodkinson, D McAlpine, S Goodacre, PA Bath, ...
PLOS Digital Health 2 (9), e0000309, 2023
Mandates: Bill & Melinda Gates Foundation, US National Institutes of Health, US Agency …
Patient and Public Involvement Toolkit: Involving LGBTQ+ Unpaid Carers
ED Zamani, L Sbaffi, T Hafford-Letchfield, S Hinchcliff, L Robers, ...
University of Sheffield, 2023
Mandates: UK Research & Innovation
Publication and funding information is determined automatically by a computer program