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
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Author Correction: 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, 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
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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
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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
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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
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Author Correction: 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
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– NEW SCIENTIST
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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
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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
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Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, AI Aviles-Rivero, C Etmann, C McCague, L Beer, JR Weir-McCall, Z Teng, E Gkrania-Klotsas, A Ruggiero, A Korhonen, E Jefferson, E Ako, G Langs, G Gozaliasl, G Yang, H Prosch, J Preller, J Stanczuk, J Tang, J Hofmanninger, J Babar, LE Sánchez, M Thillai, PM Gonzalez, P Teare, X Zhu, M Patel, C Cafolla, H Azadbakht, J Jacob, J Lowe, K Zhang, K Bradley, M Wassin, M Holzer, K Ji, MD Ortet, T Ai, N Walton, P Lio, S Stranks, T Shadbahr, W Lin, Y Zha, Z Niu, JHF Rudd, E Sala, CB Schönlieb
– Nature Machine Intelligence
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