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)
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, G Yang
– An international journal on information fusion
(2022)
82,
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence (vol 3, pg 1081, 2021)
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, MW Wang, N Holalkere, NJ Halin, IR Kamel, J Wu, X Peng, X Wang, J Shao, P Mongkolwat, J Zhang, W Liu, M Roberts, Z Teng, L Beer, LE Sanchez, E Sala, DL Rubin, A Weller, J Lasenby, C Zheng, J Wang, Z Li, C Schönlieb, T Xia
– 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 into Imaging
(2022)
13,
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.
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, IR Kamel, J Wu, X Peng, X Wang, J Shao, P Mongkolwat, J Zhang, W Liu, M Roberts, Z Teng, L Beer, LE Sanchez, E Sala, D Rubin, A Weller, J Lasenby, C Zheng, J Wang, Z Li, C-B Schönlieb, T Xia
– ArXiv
(2021)
3,
Late Breaking Abstract - Fully automated airway measurement correlates with radiological disease progression in Idiopathic Pulmonary Fibrosis
M Roberts, K Kirov, T Mclellan, E Morgan, F Kanavati, D Gallagher, P Molyneaux, C-B Schonlieb, A Ruggiero, M Thillai
– m-Health/e-health
(2021)
58,
A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images (vol 5, pg 509, 2021)
G Wang, X Liu, J Shen, C Wang, Z Li, L Ye, X Wu, T Chen, K Wang, X Zhang, Z Zhou, J Yang, Y Sang, R Deng, W Liang, T Yu, M Gao, J Wang, Z Yang, H Cai, G Lu, L Zhang, L Yang, W Xu, W Wang, A Olvera, I Ziyar, C Zhang, O Li, W Liao, J Liu, W Chen, W Chen, J Shi, L Zheng, L Zhang, Z Yan, X Zou, G Lin, G Cao, LL Lau, L Mo, Y Liang, M Roberts, E Sala, C-B Schönlieb, M Fok, JY-N Lau, T Xu, J He, K Zhang, W Li, T Lin
– Nature Biomedical Engineering
(2021)
5,
A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.
G Wang, X Liu, J Shen, C Wang, Z Li, L Ye, X Wu, T Chen, K Wang, X Zhang, Z Zhou, J Yang, Y Sang, R Deng, W Liang, T Yu, M Gao, J Wang, Z Yang, H Cai, G Lu, L Zhang, L Yang, W Xu, W Wang, A Olvera, I Ziyar, C Zhang, O Li, W Liao, J Liu, W Chen, W Chen, J Shi, L Zheng, L Zhang, Z Yan, X Zou, G Lin, G Cao, LL Lau, L Mo, Y Liang, M Roberts, E Sala, C-B Schönlieb, M Fok, JY-N Lau, T Xu, J He, K Zhang, W Li, T Lin
– Nature biomedical engineering
(2021)
5,
Machine learning for covid-19 diagnosis and prognostication: Lessons for amplifying the signal while reducing the noise
D Driggs, I Selby, M Roberts, E Gkrania-Klotsas, J Rudd, G Yang, J Babar, E Sala, C Schoenlieb
– Radiology Artificial Intelligence
(2021)
3,