Publication detail

Machine Learning-Based Pressure Ulcer Prediction in Modular Critical Care Data

ŠÍN, P. HOKYNKOVÁ, A. NOVÁKOVÁ, M. POKORNÁ, A. KRČ, R. PODROUŽEK, J.

Original Title

Machine Learning-Based Pressure Ulcer Prediction in Modular Critical Care Data

Type

journal article in Web of Science

Language

English

Original Abstract

Increasingly available open medical and health datasets encourage data-driven research with a promise of improving patient care through knowledge discovery and algorithm development. Among efficient approaches to such high-dimensional problems are a number of machine learning methods, which are applied in this paper to pressure ulcer prediction in modular critical care data. An inherent property of many health-related datasets is a high number of irregularly sampled time-variant and scarcely populated features, often exceeding the number of observations. Although machine learning methods are known to work well under such circumstances, many choices regarding model and data processing exist. In particular, this paper address both theoretical and practical aspects related to the application of six classification models to pressure ulcers, while utilizing one of the largest available Medical Information Mart for Intensive Care (MIMIC-IV) databases. Random forest, with an accuracy of 96%, is the best-performing approach among the considered machine learning algorithms.

Keywords

pressure ulcer; pressure injury; machine learning; MIMIC database; MIMIC-IV; open data; artificial neural network; random forest

Authors

ŠÍN, P.; HOKYNKOVÁ, A.; NOVÁKOVÁ, M.; POKORNÁ, A.; KRČ, R.; PODROUŽEK, J.

Released

30. 3. 2022

Publisher

MDPI

Location

Basel, Switzerland

ISBN

2075-4418

Periodical

Diagnostics

Year of study

12

Number

4

State

Swiss Confederation

Pages from

1

Pages to

13

Pages count

13

URL

https://www.mdpi.com/2075-4418/12/4/850/pdf

BibTex

@article{BUT179438,
  author="ŠÍN, P. and HOKYNKOVÁ, A. and NOVÁKOVÁ, M. and POKORNÁ, A. and KRČ, R. and PODROUŽEK, J.",
  title="Machine Learning-Based Pressure Ulcer Prediction in Modular Critical Care Data",
  journal="Diagnostics",
  year="2022",
  volume="12",
  number="4",
  pages="1--13",
  doi="10.3390/diagnostics12040850",
  issn="2075-4418",
  url="https://www.mdpi.com/2075-4418/12/4/850/pdf"
}