@inproceedings{71e9f74bb6d44f9ab4b92612b12b5a45,
title = "Using Artificial Intelligence for the Early Detection of Micro-Progression of Pressure Injuries in Hospitalized Patients: A Preliminary Nursing Perspective Evaluation",
abstract = "This study established a predictive model for the early detection of micro-progression of pressure injuries (PIs) from the perspective of nurses. An easy and programing-free artificial intelligence modeling tool with professional evaluation capability and it performed independently by nurses was used for this purpose. In the preliminary evaluation, the model achieved an accuracy of 89%. It can bring positive benefits to clinical care. Only the overfitting issue and image subtraction method remain to be addressed.",
keywords = "artificial intelligence, micro-progression, Pressure injury",
author = "Wu, {Shu Chen} and Li, {Yu Chuan Jack} and Chen, {Hsiao Ling} and Ku, {Mei Ling} and Yu, {Yen Chen} and Nguyen, {Phung Anh} and Huang, {Chih Wei}",
note = "Funding Information: This study was financially supported by the research funding of Far Eastern Memorial Hospital. Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; 18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 ; Conference date: 02-10-2021 Through 04-10-2021",
year = "2022",
month = jun,
day = "6",
doi = "10.3233/SHTI220245",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "1016--1017",
editor = "Paula Otero and Philip Scott and Martin, {Susan Z.} and Elaine Huesing",
booktitle = "MEDINFO 2021",
address = "Netherlands",
}