[PDF][PDF] Interpretable deep learning framework for predicting all-cause 30-day ICU readmissions

P Rafi, A Pakbin, SK Pentyala - Texas A&M University, 2018 - academia.edu
ICU readmissions are costly and most of the early ICU readmissions in the United States are
potentially avoidable. After the US Govts push towards reducing avoidable readmissions …

Benchmarking deep learning architectures for predicting readmission to the ICU and describing patients-at-risk

S Barbieri, J Kemp, O Perez-Concha, S Kotwal… - Scientific reports, 2020 - nature.com
To compare different deep learning architectures for predicting the risk of readmission within
30 days of discharge from the intensive care unit (ICU). The interpretability of attention …

Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory

YW Lin, Y Zhou, F Faghri, MJ Shaw, RH Campbell - PloS one, 2019 - journals.plos.org
Background Unplanned readmission of a hospitalized patient is an indicator of patients'
exposure to risk and an avoidable waste of medical resources. In addition to hospital …

Building prediction models for 30-day readmissions among icu patients using both structured and unstructured data in electronic health records

A Moerschbacher, Z He - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
ICU readmissions are associated with poor outcomes for patients and poor performance of
hospitals. Patients who are readmitted have an increased risk of in-hospital deaths; …

Explainable Machine Learning for ICU Readmission Prediction

A de Sá, D Gould, A Fedyukova, M Nicholas… - arXiv preprint arXiv …, 2023 - arxiv.org
The intensive care unit (ICU) comprises a complex hospital environment, where decisions
made by clinicians have a high level of risk for the patients' lives. A comprehensive care …

Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health records

T Zebin, TJ Chaussalet - 2019 IEEE conference on …, 2019 - ieeexplore.ieee.org
There has been a steady growth in machine learning research in healthcare, however,
progress is difficult to measure because of the use of different cohorts, task definitions and …

Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach

X Gao, S Alam, P Shi, F Dexter, N Kong - BMC medical informatics and …, 2023 - Springer
Background Advanced machine learning models have received wide attention in assisting
medical decision making due to the greater accuracy they can achieve. However, their …

HFS‐LightGBM: A machine learning model based on hybrid feature selection for classifying ICU patient readmissions

Y Qiu, S Ding, N Yao, D Gu, X Li - Expert Systems, 2021 - Wiley Online Library
Compared to patients readmitted to general wards, readmitted patients in the intensive care
unit (ICU) are exposed to higher mortality rates and prolonged hospital stays. Moreover, the …

Use of Deep Learning for Continuous Prediction of Mortality for All Admissions in Intensive Care Units

G Zeng, J Zhuang, H Huang, M Tian… - Tsinghua Science …, 2023 - ieeexplore.ieee.org
The mortality rate in the intensive care unit (ICU) is a key metric of hospital clinical quality. To
enhance hospital performance, many methods have been proposed for the stratification of …

Explainable time-series deep learning models for the prediction of mortality, prolonged length of stay and 30-day readmission in intensive care patients

Y Deng, S Liu, Z Wang, Y Wang, Y Jiang, B Liu - Frontiers in Medicine, 2022 - frontiersin.org
Background In-hospital mortality, prolonged length of stay (LOS), and 30-day readmission
are common outcomes in the intensive care unit (ICU). Traditional scoring systems and …