Search Results for author: Kenneth Jung

Found 6 papers, 2 papers with code

Predicting Inpatient Discharge Prioritization With Electronic Health Records

no code implementations2 Dec 2018 Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Ng, Nigam H. Shah

Identifying patients who will be discharged within 24 hours can improve hospital resource management and quality of care.

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data

no code implementations9 Aug 2018 Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah

We present experiments that elucidate when multitask learning with neural nets improves performance for phenotyping using EHR data relative to neural nets trained for a single phenotype and to well-tuned logistic regression baselines.

Countdown Regression: Sharp and Calibrated Survival Predictions

1 code implementation21 Jun 2018 Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Ng

Probabilistic survival predictions from models trained with Maximum Likelihood Estimation (MLE) can have high, and sometimes unacceptably high variance.

Decision Making Mortality Prediction +1

Improving Palliative Care with Deep Learning

no code implementations17 Nov 2017 Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Ng, Nigam H. Shah

The algorithm is a Deep Neural Network trained on the EHR data from previous years, to predict all-cause 3-12 month mortality of patients as a proxy for patients that could benefit from palliative care.

Some methods for heterogeneous treatment effect estimation in high-dimensions

1 code implementation1 Jul 2017 Scott Powers, Junyang Qian, Kenneth Jung, Alejandro Schuler, Nigam H. Shah, Trevor Hastie, Robert Tibshirani

When devising a course of treatment for a patient, doctors often have little quantitative evidence on which to base their decisions, beyond their medical education and published clinical trials.

Effective Representations of Clinical Notes

no code implementations19 May 2017 Sebastien Dubois, Nathanael Romano, David C. Kale, Nigam Shah, Kenneth Jung

We used the learned representations, along with commonly used bag of words and topic model representations, as features for predictive models of clinical events.

Feature Engineering Transfer Learning

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