[HTML][HTML] An AdaBoost-based algorithm to detect hospital-acquired pressure injury in the presence of conflicting annotations

JC Ho, M Sotoodeh, W Zhang, RL Simpson… - Computers in Biology …, 2024 - Elsevier
Hospital-acquired pressure injury is one of the most harmful events in clinical settings.
Patients who do not receive early prevention and treatment can experience a significant …

Investigating the potential for machine learning prediction of patient outcomes: a retrospective study of hospital acquired pressure injuries

JJ Levy, JF Lima, MW Miller, GL Freed, AJ O'Malley… - medRxiv, 2020 - medrxiv.org
Background While recent research efforts to reduce pressure ulcers in the clinical context
have focused on key retrospective characteristics, little work has focused on creating real …

[HTML][HTML] Machine learning approaches for hospital acquired pressure injuries: a retrospective study of electronic medical records

JJ Levy, JF Lima, MW Miller, GL Freed… - Frontiers in Medical …, 2022 - frontiersin.org
Background Many machine learning heuristics integrate well with Electronic Medical Record
(EMR) systems yet often fail to surpass traditional statistical models for biomedical …

Predicting pressure injury using nursing assessment phenotypes and machine learning methods

W Song, MJ Kang, L Zhang, W Jung… - Journal of the …, 2021 - academic.oup.com
Objective Pressure injuries are common and serious complications for hospitalized patients.
The pressure injury rate is an important patient safety metric and an indicator of the quality of …

[HTML][HTML] The predictive effect of different machine learning algorithms for pressure injuries in hospitalized patients: A network meta-analyses

C Qu, W Luo, Z Zeng, X Lin, X Gong, X Wang, Y Zhang… - Heliyon, 2022 - cell.com
Background Pressure injury has always been a focus and difficulty of nursing. With the
development of nursing informatization, a large amount of structured and unstructured data …

Predicting pressure injury in critical care patients: a machine-learning model

J Alderden, GA Pepper, A Wilson, JD Whitney… - American Journal of …, 2018 - AACN
Background Hospital-acquired pressure injuries are a serious problem among critical care
patients. Some can be prevented by using measures such as specialty beds, which are not …

[HTML][HTML] Modeling and prediction of pressure injury in hospitalized patients using artificial intelligence

C Anderson, Z Bekele, Y Qiu, D Tschannen… - BMC Medical Informatics …, 2021 - Springer
Background Hospital-acquired pressure injuries (PIs) induce significant patient suffering,
inflate healthcare costs, and increase clinical co-morbidities. PIs are mostly due to bed …

Leveraging artificial intelligence and decision support systems in hospital-acquired pressure injuries prediction: A comprehensive review

KM Toffaha, MCE Simsekler, MA Omar - Artificial Intelligence in Medicine, 2023 - Elsevier
Background: Hospital-acquired pressure injuries (HAPIs) constitute a significant challenge
harming thousands of people worldwide yearly. While various tools and methods are used …

Development and validation of a machine learning algorithm–based risk prediction model of pressure injury in the intensive care unit

J Xu, D Chen, X Deng, X Pan, Y Chen… - International wound …, 2022 - Wiley Online Library
The study aimed to establish a machine learning–based scoring nomogram for early
recognition of likely pressure injuries in an intensive care unit (ICU) using large‐scale …

[HTML][HTML] Dynamic risk prediction for hospital-acquired pressure injury in adult critical care patients

AM Shui, P Kim, V Aribindi, CY Huang… - Critical Care …, 2021 - journals.lww.com
OBJECTIVES: To develop and validate a dynamic risk prediction model to estimate the risk
of developing a hospital-acquired pressure injury among adult ICU patients. DESIGN: ICU …