Predicting Mortality of ICU Patients

The papers below were presented at Computers in Cardiology 2012. Please cite this publication when referencing any of these papers. These papers have been made available by their authors under the terms of the Creative Commons Attribution License 3.0 (CCAL). We wish to thank all of the authors for their contributions.

The first of these papers is an introduction to the challenge topic, with a summary of the challenge results and a discussion of their implications.

Predicting In-Hospital Mortality of Patients in ICU: The PhysioNet/Computing in Cardiology Challenge 2012
Ikaro Silva, George Moody, Daniel J Scott, Leo A Celi, Roger G Mark

The remaining papers were presented by participants in the Challenge, who describe their approaches to the challenge problem.

Patient Specific Predictions in the Intensive Care Unit using a Bayesian Ensemble
Alistair EW Johnson, Nic Dunkley, Louis Mayaud, Athanasios Tsanas, Andrew A Kramer, Gari D Clifford

An Imputation-Enhanced Algorithm for ICU Mortality Prediction
Cheng H Lee, Natalia M Arzeno, Joyce C Ho, Haris Vikalo

PhysioNet 2012 Challenge: Predicting Mortality of ICU Patients using a Cascaded SVM-GLM Paradigm
Luca Citi, Riccardo Barbieri

A Neural Network Model for Mortality Prediction in ICU
Henian Xia, Brian J Daley, Adam Petrie, Xiaopeng Zhao

ICU Mortality Prediction using Time Series Motifs
Sean McMillan, Chih-Chun Chia, Alexander Van Esbroeck, Ilan Rubinfeld, Zeeshan Syed

Prediction of Mortality in an Intensive Care Unit using Logistic Regression and a Hidden Markov Model
Srinivasan Vairavan, Larry Eshelman, Syed Haider, Abigail Flowers, Adam Seiver

CinC Challenge: Predicting In-hospital Mortality of Intensive Care Unit by Analyzing Histogram of Medical Variables under Cascaded Adaboost Model
Chucai Yi, Yi Sun, Yingli Tian

Combining Machine Learning and Clinical Rules to Build an Algorithm for Predicting ICU Mortality Risk
Michael Krajnak, Joel Xue, Willi Kaiser, William Balloni

Towards the Prediction of Mortality in Intensive Care Units Patients: a Simple Correspondence Analysis Approach
Erika Severeyn, Miguel Altuve, Francisco Ng, Carlos Lollett, Sara Wong

Linear Bayes Classification for Mortality Prediction
Martin Macas, Jakub Kuzilek, Tadeáš Odstrčilík, Michal Huptych

Robust Prediction of Patient Mortality from 48 Hour ICU Data
Luigi Y Di Marco, Marjan Bojarnejad, Susan T King, Wenfeng Duan, Costanzo Di Maria, Dingchang Zheng, Alan Murray, Philip Langley

Predicting Mortality of ICU Patients using Statistics of Physiological Variables and Support Vector Machines
Antonio Bosnjak, Guillermo Montilla

2012 PhysioNet Challenge: An Artificial Neural Network to Predict Mortality in ICU Patients and Application of Solar Physics Analysis Methods
Tom J Pollard, Louise Harra, David Williams, Steve Harris, Demetrio Martinez, Kevin Fong

Predicting In-Hospital-Death and Mortality Percentage using Logistic Regression
Steven L Hamilton, James R Hamilton

Mortality Risk Assessment for ICU Patients using Logistic Regression
Deep Bera, Mithun Manjnath Nayak

CinC Challenge: Cluster Analysis of Multi-Granular Time-Series Data for Mortality Rate Prediction
Jianfeng Xu, Dan Li, Yuanjian Zhang, Admir Djulovic, Yu Li, Youjie Zeng