Data-driven multivariate cohort selection and automated CT scan lung volume measurement identifies disease progression in Idiopathic Pulmonary Fibrosis (IPF)
H Manners, T Mclellan, K Kirov, M Roberts, F Kanavati, G Mckenzie, D Gallagher, J Hainsworth, D Dosanjh, P Molyneaux, A Ruggiero, M Thillai
– 12.01 - Idiopathic interstitial pneumonias
(2022)
60,
GLPG1205 shows reduction in lung volume decline over 26 weeks vs placebo when measured with novel volumetric CT analysis in IPF patients
M Thillai, K Kirov, E Santermans, M Roberts, P Molyneaux, F Kanavati, D Gallagher, A De Haas-Amatsaleh, T Van der Aa, P Ford, C Seemayer, B Van den Blink, A Ruggiero
– 12.01 - Idiopathic interstitial pneumonias
(2022)
60,
USING ARTIFICIAL INTELLIGENCE TO INTERROGATE MULTI-NATIONAL IMAGING DATASETS TO DETERMINE THE MECHANISM OF COVID-19 PNEUMOTHORAX
IA Selby, D Driggs, V Majcher, M Roberts, LE Sanchez, JHF Rudd, E Sala, C Bibiane-Schonlieb, SJ Marciniak, J Babar
– ‘Infinity War’ – Ongoing clinical challenges in COVID-19
(2022)
77,
Navigating the challenges in creating complex data systems: a development philosophy
S Dittmer, M Roberts, J Gilbey, A Biguri, AIX-COVNET Collaboration, J Preller, JHF Rudd, JAD Aston, C-B Schönlieb
(2022)
Classification of datasets with imputed missing values: does imputation quality matter?
T Shadbahr, M Roberts, J Stanczuk, J Gilbey, P Teare, S Dittmer, M Thorpe, RV Torne, E Sala, P Lio, M Patel, AIX-COVNET Collaboration, JHF Rudd, T Mirtti, A Rannikko, JAD Aston, J Tang, C-B Schönlieb
(2022)
146 Ct radiomics in carotid artery atherosclerosis: a systematic evaluation of robustness, reproducibility and predictive performance for culprit lesions
E Le, L Rundo, J Tarkin, N Evans, M Chowdhury, P Coughlin, H Pavey, C Wall, F Zaccagna, F Gallagher, Y Huang, R Sriranjan, A Le, J Weir-McCall, M Roberts, F Gilbert, E Warburton, C-B Schonlieb, E Sala, J Rudd
– Imaging
(2022)
108,
Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
Y Nan, JD Ser, S Walsh, C Schönlieb, M Roberts, I Selby, K Howard, J Owen, J Neville, J Guiot, B Ernst, A Pastor, A Alberich-Bayarri, MI Menzel, S Walsh, W Vos, N Flerin, J-P Charbonnier, E van Rikxoort, A Chatterjee, H Woodruff, P Lambin, L Cerdá-Alberich, L Martí-Bonmatí, F Herrera et al.
– An international journal on information fusion
(2022)
82,
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence (Nature Machine Intelligence, (2021), 3, 12, (1081-1089), 10.1038/s42256-021-00421-z)
X Bai, H Wang, L Ma, Y Xu, J Gan, Z Fan, F Yang, K Ma, J Yang, S Bai, C Shu, X Zou, R Huang, C Zhang, X Liu, D Tu, C Xu, W Zhang, X Wang, A Chen, Y Zeng, D Yang, M-W Wang, N Holalkere, NJ Halin et al.
– Nature machine intelligence
(2022)
4,
Comparative Performance of Fully-Automated and Semi-Automated Artificial Intelligence Methods for the Detection of Clinically Significant Prostate Cancer on MRI: a Systematic Review
N Sushentsev, N Moreira Da Silva, M Yeung, T Barrett, E Sala, M Roberts, L Rundo
– Insights Imaging
(2022)
13,
Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review
N Sushentsev, N Moreira Da Silva, M Yeung, T Barrett, E Sala, M Roberts, L Rundo
– Insights into Imaging
(2022)
13,
