Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

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Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting.Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

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Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

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2017 nî lūn-bûn

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Machine Learning for Healthcar ...... ft in Healthcare Epidemiology.

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Machine Learning for Healthcar ...... ft in Healthcare Epidemiology.

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Erica S Shenoy

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Jenna Wiens

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Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients

Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012

Dermatologist-level classification of skin cancer with deep neural networks

A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions

Creating value in health care through big data: opportunities and policy implications.

Big data in health care: using analytics to identify and manage high-risk and high-cost patients.

Data-driven decisions for reducing readmissions for heart failure: general methodology and case study.

Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile.

A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data.

Learning Instance-Specific Predictive Models

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scholarly article

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10.1093/CID/CIX731

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English

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2017-08-21T00:00:00Z

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29020316

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machine learning

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5850539

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Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

about

P2860

P2860

Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

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