Building ICU In-hospital Mortality Prediction Model with Federated Learning

[1]  W. Knaus,et al.  APACHE II: a severity of disease classification system. , 1985 .

[2]  Alistair E. W. Johnson,et al.  The eICU Collaborative Research Database, a freely available multi-center database for critical care research , 2018, Scientific Data.

[3]  Aaron Roth,et al.  The Algorithmic Foundations of Differential Privacy , 2014, Found. Trends Theor. Comput. Sci..

[4]  Xiang Li,et al.  On the Convergence of FedAvg on Non-IID Data , 2019, ICLR.

[5]  Daniel L. Rubin,et al.  Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions , 2017, Journal of Digital Imaging.

[6]  Kenneth D. Mandl,et al.  FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record , 2018, ArXiv.

[7]  R. Bellomo,et al.  The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). , 2016, JAMA.

[8]  Li Huang,et al.  Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records , 2019, J. Biomed. Informatics.

[9]  Anit Kumar Sahu,et al.  Federated Optimization in Heterogeneous Networks , 2018, MLSys.

[10]  Peter Bühlmann,et al.  MissForest - non-parametric missing value imputation for mixed-type data , 2011, Bioinform..

[11]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[12]  Qiang Yang,et al.  Federated Machine Learning , 2019, ACM Trans. Intell. Syst. Technol..

[13]  S. Lemeshow,et al.  A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study , 1993 .

[14]  Anna Veronika Dorogush,et al.  CatBoost: unbiased boosting with categorical features , 2017, NeurIPS.

[15]  Andrew M. Dai,et al.  Federated and Differentially Private Learning for Electronic Health Records , 2019, ArXiv.

[16]  Peter Richtárik,et al.  Federated Optimization: Distributed Machine Learning for On-Device Intelligence , 2016, ArXiv.

[17]  Blaise Agüera y Arcas,et al.  Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.

[18]  Aníbal R. Figueiras-Vidal,et al.  Pattern classification with missing data: a review , 2010, Neural Computing and Applications.