Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study von Baqui, Pedro, Bica, Ioana, Marra, Valerio, Ercole, Ari, van der Schaar, Mihaela

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Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data von Imrie, Fergus, Bradley, Anthony R, van der Schaar, Mihaela, Deane, Charlotte M

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Data-Driven Online Recommender Systems With Costly Information Acquisition von Atan, Onur, Ghoorchian, Saeed, Maghsudi, Setareh, van der Schaar, Mihaela

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Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors von Baqui, Pedro, Marra, Valerio, Alaa, Ahmed M., Bica, Ioana, Ercole, Ari, van der Schaar, Mihaela

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A systematic framework for dynamically optimizing multi-user wireless video transmission von Fu, Fangwen, Van Der Schaar, Mihaela

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Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study von Callender, Thomas, Imrie, Fergus, Cebere, Bogdan, Pashayan, Nora, Navani, Neal, van der Schaar, Mihaela, Janes, Sam M

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Dynamic network formation with foresighted agents von Song, Yangbo, van der Schaar, Mihaela

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From Real‐World Patient Data to Individualized Treatment Effects Using Machine Learning: Current and Future Methods to Address Underlying Challenges von Bica, Ioana, Alaa, Ahmed M., Lambert, Craig, Schaar, Mihaela

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Collaborative resource exchanges for peer-to-peer video streaming over wireless mesh networks von Mastronarde, Nicholas, Turaga, Deepak S., van der Schaar, Mihaela

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Personalized Course Sequence Recommendations von Jie Xu, Tianwei Xing, van der Schaar, Mihaela

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External validity of machine learning-based prognostic scores for cystic fibrosis: A retrospective study using the UK and Canadian registries von Qin, Yuchao, Alaa, Ahmed, Floto, Andres, Schaar, Mihaela van der

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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants von Alaa, Ahmed M, Bolton, Thomas, Di Angelantonio, Emanuele, Rudd, James H F, van der Schaar, Mihaela

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How artificial intelligence and machine learning can help healthcare systems respond to COVID-19 von van der Schaar, Mihaela, Alaa, Ahmed M., Floto, Andres, Gimson, Alexander, Scholtes, Stefan, Wood, Angela, McKinney, Eoin, Jarrett, Daniel, Lio, Pietro, Ercole, Ari

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A Novel, Potentially Universal Machine Learning Algorithm to Predict Complications in Total Knee Arthroplasty von Devana, Sai K., Shah, Akash A., Lee, Changhee, Roney, Andrew R., van der Schaar, Mihaela, SooHoo, Nelson F.

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Between-centre differences for COVID-19 ICU mortality from early data in England von Qian, Zhaozhi, Alaa, Ahmed M., van der Schaar, Mihaela, Ercole, Ari

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Generalized Phase Shifting for M -Band Discrete Wavelet Packet Transforms von Andreopoulos, Y., van der Schaar, M.

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CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 von Qian, Zhaozhi, Alaa, Ahmed M., van der Schaar, Mihaela

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Sex-Related Differences in Heart Failure After ST-Segment Elevation Myocardial Infarction von Cenko, Edina, van der Schaar, Mihaela, Yoon, Jinsung, Manfrini, Olivia, Vasiljevic, Zorana, Vavlukis, Marija, Kedev, Sasko, Miličić, Davor, Badimon, Lina, Bugiardini, Raffaele

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Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements von Devana, Sai K, Shah, Akash A, Lee, Changhee, Jensen, Andrew R, Cheung, Edward, van der Schaar, Mihaela, SooHoo, Nelson F

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Improving Workflow Efficiency for Mammography Using Machine Learning von Kyono, Trent, Gilbert, Fiona J., van der Schaar, Mihaela

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