most citedThe Dependence of Machine Learning on Electronic Medical Record Quality

27 citations · 42 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2019

Interpreting a Recurrent Neural Network's Predictions of ICU Mortality Risk

Long V. Ho, Melissa D. Aczon, David Ledbetter +1

Deep learning has demonstrated success in many applications; however, their use in healthcare has been limited due to the lack of transparency into how they generate predictions. A…

stat.ML20192 cited

The Impact of Extraneous Variables on the Performance of Recurrent Neural Network Models in Clinical Tasks

Eugene Laksana, Melissa Aczon, Long Ho +3

Electronic Medical Records (EMR) are a rich source of patient information, including measurements reflecting physiologic signs and administered therapies. Identifying which variabl…

stat.ML2017

Predicting Individual Physiologically Acceptable States for Discharge from a Pediatric Intensive Care Unit

Cameron Carlin, Long Van Ho, David Ledbetter +2

Objective: Predict patient-specific vitals deemed medically acceptable for discharge from a pediatric intensive care unit (ICU). Design: The means of each patient's hr, sbp and dbp…

stat.ML201727 cited

The Dependence of Machine Learning on Electronic Medical Record Quality

Long Ho, David Ledbetter, Melissa Aczon +1

There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). Across different institutions, however, EMR quality can vary widely. This work i…

stat.ML201713 cited

Prediction of Kidney Function from Biopsy Images Using Convolutional Neural Networks

David Ledbetter, Long Ho, Kevin V Lemley

A Convolutional Neural Network was used to predict kidney function in patients with chronic kidney disease from high-resolution digital pathology scans of their kidney biopsies. Ki…