Unplanned Readmission

Unplanned hospital readmission, the re-hospitalization of patients shortly after discharge, is a significant healthcare problem impacting patient outcomes and resource allocation. Current research focuses on developing accurate and interpretable predictive models using machine learning, particularly deep learning architectures like multilayer perceptrons, convolutional LSTMs, and random forests, often incorporating natural language processing of electronic health records to extract relevant clinical information. These models aim to identify at-risk patients enabling timely interventions and improved care pathways, ultimately reducing readmission rates and associated costs. The development of explainable AI methods is crucial for building trust and facilitating clinical adoption of these predictive tools.

Papers

March 12, 2024

Enhancing Readmission Prediction with Deep Learning: Extracting Biomedical Concepts from Clinical Texts
Rasoul Samani, Mohammad Dehghani, Fahime Shahrokh
Deep Learning Clinical Text Biomedical Concept Readmission Prediction Hospital Readmission Unplanned Readmission Patient Readmission

October 16, 2023

An Interpretable Deep-Learning Framework for Predicting Hospital Readmissions From Electronic Health Records
Fabio Azzalini, Tommaso Dolci, Marco Vagaggini
Deep Learning Electronic Health Record Interpretable Deep Learning Hospital Readmission Unplanned Readmission Hospital Readmission Prediction

September 25, 2023

Explainable Machine Learning for ICU Readmission Prediction
Alex G. C. de Sá, Daniel Gould, Anna Fedyukova, Mitchell Nicholas, Lucy Dockrell, Calvin Fletcher, David Pilcher, Daniel Capurro, David B. Ascher, Khaled El-Khawas, Douglas E. V. Pires
Intensive Care Unit Explainable Machine Learning Intensive Care Readmission Prediction Unplanned Readmission Patient Readmission

June 29, 2023

Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learning
Yuelyu Ji, Yuhe Gao, Runxue Bao, Qi Li, Disheng Liu, Yiming Sun, Ye Ye
Human Prediction Patient Friendly Language Multi Source Heterogeneous Clinical Coronavirus Disease 2019 Emergency Department Unplanned Readmission

May 14, 2023

Predicting Unplanned Readmissions in the Intensive Care Unit: A Multimodality Evaluation
Eitam Sheetrit, Menachem Brief, Oren Elisha
Intensive Care Unit Multimodal Evaluation Readmission Prediction Hospital Readmission Unplanned Readmission

June 30, 2022

Advances in Prediction of Readmission Rates Using Long Term Short Term Memory Networks on Healthcare Insurance Data
Shuja Khalid, Francisco Matos, Ayman Abunimer, Joel Bartlett, Richard Duszak, Michal Horny, Judy Gichoya, Imon Banerjee, Hari Trivedi
Human Prediction Long Short Term Memory Healthcare Data Hospital Readmission Unplanned Readmission Patient Readmission

January 10, 2022

A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu
Variable Selection Interpretable Machine Variable Importance Year Specific Mortality Surface Unplanned Readmission

Unplanned Readmission

Papers

Enhancing Readmission Prediction with Deep Learning: Extracting Biomedical Concepts from Clinical Texts

An Interpretable Deep-Learning Framework for Predicting Hospital Readmissions From Electronic Health Records

Explainable Machine Learning for ICU Readmission Prediction

Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learning

Predicting Unplanned Readmissions in the Intensive Care Unit: A Multimodality Evaluation

Advances in Prediction of Readmission Rates Using Long Term Short Term Memory Networks on Healthcare Insurance Data

A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study