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Harry Askham
Harry Askham
DeepMind
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Title
Cited by
Cited by
Year
Clinically applicable deep learning for diagnosis and referral in retinal disease
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
Nature medicine 24 (9), 1342-1350, 2018
22242018
A clinically applicable approach to continuous prediction of future acute kidney injury
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
Nature 572 (7767), 116-119, 2019
8252019
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
3482023
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ...
arXiv preprint arXiv:1809.04430, 2018
3142018
Predicting conversion to wet age-related macular degeneration using deep learning
J Yim, R Chopra, T Spitz, J Winkens, A Obika, C Kelly, H Askham, M Lukic, ...
Nature Medicine 26 (6), 892-899, 2020
2232020
Tweetlda: supervised topic classification and link prediction in twitter
D Quercia, H Askham, J Crowcroft
Proceedings of the 4th Annual ACM Web Science Conference, 247-250, 2012
1862012
Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study
S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ...
Journal of medical Internet research 23 (7), e26151, 2021
1452021
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
N Tomašev, N Harris, S Baur, A Mottram, X Glorot, JW Rae, M Zielinski, ...
Nature Protocols 16 (6), 2765-2787, 2021
592021
Generalizable medical image analysis using segmentation and classification neural networks
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
US Patent 10,198,832, 2019
442019
Generalizable medical image analysis using segmentation and classification neural networks
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
US Patent 10,878,601, 2020
62020
3-D convolutional neural networks for organ segmentation in medical images for radiotherapy planning
S Nikolov, S Blackwell, J De Fauw, B Romera-Paredes, CL Meyer, ...
US Patent 11,100,647, 2021
52021
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
32024
Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
22019
3-D convolutional neural networks for organ segmentation in medical images for radiotherapy planning
S Nikolov, S Blackwell, J De Fauw, B Romera-Paredes, CL Meyer, ...
US Patent 11,676,281, 2023
2023
Prediction of future adverse health events using neural networks by pre-processing input sequences to include presence features
N Tomasev, X Glorot, JW Rae, M Zielinski, A Mottram, H Askham, ...
US Patent 11,302,446, 2022
2022
Generalizable medical image analysis using segmentation and classification neural networks
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
US Patent App. 17/114,586, 2021
2021
Diagnostic accuracy and interobserver variability of macular disease evaluation using optical coherence tomography
SK Wagner, R Chopra, JR Ledsam, H Askham, S Blackwell, L Faes, ...
Investigative Ophthalmology & Visual Science 60 (9), 1849-1849, 2019
2019
Clinically applicable deep learning for diagnosis and referral in retinal optical coherence tomography
J De Fauw, J Ledsam, BR Paredes, SN Nikolov, N Tomašev, SJ Blackwell, ...
2018
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