Data Science

The feasibility and acceptability of automated feedback and deliberate practice in psychological therapies for anxiety and depression

Authors Sam Malins, Grazziela Figueredo, David Saxon, Kate Horton, Jeremie Clos, Thomas Trimble, Kavan Fatehi, David…
The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management.

Authors Faboya, Olusola; Figueredo, Grazziela; Ryan, Brendan; Siebers, Peer-Olaf. Abstract The uneven utilisation of modes of…
Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep.

Authors Kaler J, Mitsch J, Vázquez-Diosdado JA, Bollard N, Dottorini T, Ellis KA. Abstract Lameness in…
Study protocol for a multicentre longitudinal mixed methods study to explore the Outcomes of ChildrEn and fAmilies in the first year after paediatric Intensive Care: the OCEANIC study

Authors Manning, J. C., Latour, J. M., Curley, M. A. Q., Draper, E. S., Jilani, T.,…
Cardiac TdP risk stratification modelling of anti-infective compounds including chloroquine and hydroxychloroquine

Authors Whittaker Dominic G., Capel Rebecca A., Hendrix Maurice, Chan Xin Hui S., Herring Neil, White…
Circulating fibrocytes are not disease-specific prognosticators in idiopathic pulmonary fibrosis

Authors Stewart, I. D. et al. Abstract In people with idiopathic pulmonary fibrosis, circulating fibrocytes ≥2.2%…
Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis

Authors Chernbumroong, S. et al. Abstract Background: Lymphangioleiomyomatosis (LAM) is a rare multisystem disease with variable clinical…
Mass spectrometry and machine learning for the accurate diagnosis of benzylpenicillin and multidrug resistance of Staphylococcus aureus in bovine mastitis

Authors Esener, N., Maciel-Guerra, A., Giebel, K., Lea, D., Green, M. J., Bradley, A. J. and…
Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning

Authors Maciel-Guerra, A., Esener, N., Giebel, K., Lea, D., Green, M. J., Bradley, A. J. and…
Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP

Authors Quinlan, P. R. et al. Abstract Our cluster analysis of the Cancer Genome Atlas for…