@article{9a2db8d5e6554968ad496e93e557fb28,
title = "Machine Learning in Pain Medicine: An Up-To-Date Systematic Review",
abstract = "Introduction: Pain is the unpleasant sensation and emotional experience that leads to poor quality of life for millions of people worldwide. Considering the complexity in understanding the principles of pain and its significant impact on individuals and society, research focuses to deliver innovative pain relief methods and techniques. This review explores the clinical uses of machine learning (ML) for the diagnosis, classification, and management of pain. Methods: A systematic review of the current literature was conducted using the PubMed database library. Results: Twenty-six papers related to pain and ML research were included. Most of the studies used ML for effectively classifying the patients{\textquoteright} level of pain, followed by use of ML for the prediction of manifestation of pain and for pain management. A less common reason for performing ML analysis was for the diagnosis of pain. The different approaches are thoroughly discussed. Conclusion: ML is increasingly used in pain medicine and appears to be more effective compared to traditional statistical approaches in the diagnosis, classification, and management of pain.",
keywords = "Algorithms, Machine learning, Pain, Pain classification, Pain diagnosis, Pain management, Pain manifestation, Supervised learning, Unsupervised learning",
author = "Maria Matsangidou and Andreas Liampas and Melpo Pittara and Pattichi, {Constantinos S.} and Panagiotis Zis",
note = "Funding Information: No funding or sponsorship was received for this study or publication of this article. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published. Maria Matsangidou, Data analysis and interpretation, Drafting the article. Andreas Liampas, Data Collection. Drafting the article. Melpo Pittara, Data Collection. Constantinos S. Pattichi, Critical revision of the article. Panagiotis Zis, Conception or design of the work, data collection, data analysis, data interpretation, critical revision of the article. Maria Matsangidou, Andreas Liampas, Melpo Pittara, Constantinos S. Pattichi and Panagiotis Zis have nothing to disclose. This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = dec,
doi = "10.1007/s40122-021-00324-2",
language = "English",
volume = "10",
pages = "1067--1084",
journal = "Pain and Therapy",
issn = "2193-8237",
number = "2",
}