Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology
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[1] Jenna Wiens,et al. Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach , 2016, J. Mach. Learn. Res..
[2] D. Koller,et al. Integration of Early Physiological Responses Predicts Later Illness Severity in Preterm Infants , 2010, Science Translational Medicine.
[3] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Pardis Sabeti,et al. Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients , 2016, PLoS neglected tropical diseases.
[5] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[6] Jenna Wiens,et al. Active Learning Applied to Patient-Adaptive Heartbeat Classification , 2010, NIPS.
[7] F. Cabitza,et al. Unintended Consequences of Machine Learning in Medicine , 2017, JAMA.
[8] John M. Drake,et al. Rodent reservoirs of future zoonotic diseases , 2015, Proceedings of the National Academy of Sciences.
[9] B. Opmeer. Electronic Health Records as Sources of Research Data. , 2016, JAMA.
[10] D. Anderson,et al. Guidance for Infection Prevention and Healthcare Epidemiology Programs: Healthcare Epidemiologist Skills and Competencies , 2015, Infection Control & Hospital Epidemiology.
[11] Yan Liu,et al. An Examination of Multivariate Time Series Hashing with Applications to Health Care , 2014, 2014 IEEE International Conference on Data Mining.
[12] Xiang Wang,et al. Unsupervised learning of disease progression models , 2014, KDD.
[13] Byron C. Wallace,et al. Identifying Differences in Physician Communication Styles with a Log-Linear Transition Component Model , 2014, AAAI.
[14] Shyam Visweswaran,et al. Learning Instance-Specific Predictive Models , 2010, J. Mach. Learn. Res..
[15] Ella S. Franklin,et al. Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile , 2014, Open forum infectious diseases.
[16] Jack Parkinson,et al. The Role of the World Bank , 1981 .
[17] Byron C. Wallace,et al. Extracting PICO Sentences from Clinical Trial Reports using Supervised Distant Supervision , 2016, J. Mach. Learn. Res..
[18] M. Levy,et al. Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2008 , 2007, Intensive Care Medicine.
[19] P. Pronovost,et al. A targeted real-time early warning score (TREWScore) for septic shock , 2015, Science Translational Medicine.
[20] Joachim Roski,et al. Creating value in health care through big data: opportunities and policy implications. , 2014, Health affairs.
[21] D. Bates,et al. Big data in health care: using analytics to identify and manage high-risk and high-cost patients. , 2014, Health affairs.
[22] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[23] Andrew Y. Ng,et al. Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks , 2017, ArXiv.
[24] Carla E. Brodley,et al. Decrypting "Cryptogenic" Epilepsy: Semi-supervised Hierarchical Conditional Random Fields For Detecting Cortical Lesions In MRI-Negative Patients , 2016, J. Mach. Learn. Res..
[25] Mitchell M. Levy,et al. Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock , 2004, Critical care medicine.
[26] Jenna Wiens,et al. Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task , 2012, NIPS.
[27] Ali H. Shoeb,et al. Application of Machine Learning To Epileptic Seizure Detection , 2010, ICML.
[28] Jenna Wiens,et al. A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions , 2014, J. Am. Medical Informatics Assoc..
[29] Wei Xu,et al. Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation , 2016, TACL.
[30] C. Sprung,et al. Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock, 2012 , 2013, Intensive Care Medicine.
[31] Mark Braverman,et al. Data-Driven Decisions for Reducing Readmissions for Heart Failure: General Methodology and Case Study , 2014, PloS one.
[32] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[33] Peter Szolovits,et al. A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data , 2015, AAAI.
[34] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[35] M. Ghassemi,et al. Predicting early psychiatric readmission with natural language processing of narrative discharge summaries , 2016, Translational psychiatry.