[HTML][HTML] State of the art of machine learning–enabled clinical decision support in intensive care units: literature review

N Hong, C Liu, J Gao, L Han, F Chang… - JMIR medical …, 2022 - medinform.jmir.org
Background Modern clinical care in intensive care units is full of rich data, and machine
learning has great potential to support clinical decision-making. The development of …

[HTML][HTML] Predictive modeling for readmission to intensive care: a systematic review

MM Ruppert, TJ Loftus, C Small, H Li… - Critical Care …, 2023 - journals.lww.com
OBJECTIVES: To evaluate the methodologic rigor and predictive performance of models
predicting ICU readmission; to understand the characteristics of ideal prediction models; and …

Early hospital mortality prediction using vital signals

R Sadeghi, T Banerjee, W Romine - Smart Health, 2018 - Elsevier
Early hospital mortality prediction is critical as intensivists strive to make efficient medical
decisions about the severely ill patients staying in intensive care units (ICUs). As a result …

Explainable machine learning on AmsterdamUMCdb for ICU discharge decision support: uniting intensivists and data scientists

PJ Thoral, M Fornasa, DP De Bruin… - Critical care …, 2021 - journals.lww.com
Objectives: Unexpected ICU readmission is associated with longer length of stay and
increased mortality. To prevent ICU readmission and death after ICU discharge, our team of …

Domain adaptation using convolutional autoencoder and gradient boosting for adverse events prediction in the intensive care unit

Y Zhu, J Venugopalan, Z Zhang… - Frontiers in Artificial …, 2022 - frontiersin.org
More than 5 million patients have admitted annually to intensive care units (ICUs) in the
United States. The leading causes of mortality are cardiovascular failures, multi-organ …

Natural Language Processing for Health System Messages: Deep Transfer Learning Approach to Aspect-Based Sentiment Analysis of COVID-19 Content

M Sun - 2022 - search.proquest.com
Recent efforts in clinical natural language processing research have focused on mining
social media data and other user-generated data relevant to COVID-19. An increasing …

Entering the new digital era of intensive care medicine: an overview of interdisciplinary approaches to use artificial intelligence for patients' benefit

O Old, B Friedrichson, K Zacharowski… - European Journal of …, 2023 - journals.lww.com
The idea of implementing artificial intelligence in medicine is as old as artificial intelligence
itself. So far, technical difficulties have prevented the integration of artificial intelligence in …

Accurate and reproducible prediction of ICU readmissions

DP Nguyen, N Paris, A Parrot - MedRxiv, 2019 - medrxiv.org
Readmission in the intensive care unit (ICU) is associated with poor clinical outcomes and
high costs. Traditional scoring methods to help clinicians deciding whether a patient is ready …

IoT-based intensive care secure framework for patient monitoring and tracking

LN Omran, KA Ezzat, A Bayoumi… - … Journal of Grid …, 2019 - inderscienceonline.com
This paper aims to design a prototype of the real-time patient control system. The proposed
framework is used to quantify the physical parameters of the patient such as the temperature …

Developing a Machine Learning prediction model for bedside decision support by predicting readmission or death following discharge from the Intensive Care unit

PJ Thoral, M Fornasa, DP de Bruin, H Hovenkamp… - 2020 - researchsquare.com
Background Unexpected ICU readmission is associated with longer length of stay and an
increase in mortality. Real time support systems could prevent untimely discharge from the …