Machine learning in chronic pain research – A review

Author:

Savarimuthu Sabeenian Royappan,Meiyalagan Vinodhini Chinnayan

Publisher

AIP Publishing

Reference20 articles.

1. Marit Dagny Kristine Jenssen, Per Atle Bakkevoll, Phuong Dinh Ngo, Andrius Budrionis, Asbjorn Johansen Fagerlund, Maryam Tayefi, Johan Gustav Bellika and Fred Godtliebsen, “Machine Learning in Chronic Pain Research: A Scoping Review”, MDPI applied sciences (2021).

2. Alex Novaes Santana, Charles Novaes de Santana, Pedro Montoya, “Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment”. Diagnostics, 958 (2020).

3. Durgadevi Velusamy, S. Alagarsamy, N. Vijay, C.S. Ragul, and J. Subash, “Machine Learning Algorithms for Clinical Diagnosis of Lower Back Pain – A Survey”, ISSN:1583-6258, PP. 3993 – 4001, Vol. 25, Issue 4 (2021).

4. Max A. Kramer, “Assessing the Feasibility of Machine Learning to Predict Chronic Pain in Adolescence”, Thesis, Oberlin College (2020).

5. Mohamed Elgendi, Catherine Allaire, Christina Williams, Mohamed A. Bedaiwy and Paul J. Yong, “Machine Learning Revealed New Correlates of Chronic Pelvic Pain in Women”, Article 6006004, Vol 2 (2020).

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1. A Comprehensive Review on - Machine Learning in Bio-Signal Analysis for Chronic Pain Research;2023 International Conference on Emerging Research in Computational Science (ICERCS);2023-12-07

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