A classification algorithm to predict chronic pain using both regression and machine learning – A stepwise approach-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A classification algorithm to predict chronic pain using both regression and machine learning – A stepwise approach

Published:2021-12 Issue: Volume:62 Page:151504
ISSN:0897-1897
Container-title:Applied Nursing Research
language:en
Short-container-title:Applied Nursing Research

Author:

Tsai Pao-Feng,Wang Chih-Hsuan,Zhou Yang,Ren Jiaxiang,Jones Alisha,Watts Sarah O.,Chou Chiahung,Ku Wei-Shinn

Funder

NIH

US Department of Veterans Affairs Office of Research & Development

Publisher

Elsevier BV

Subject

General Nursing

Reference42 articles.

1. Daily pain variations among patients with hand, hip, and knee osteoarthritis;Allen;Osteoarthritis and Cartilage,2009

2. Depression and pain comorbidity: A literature review;Bair;Archives of Internal Medicine,2003

3. Monitoring the nociception level: A multi-parameter approach;Ben-Israel;Journal of Clinical Monitoring and Computing,2013

4. Biomarkers for musculoskeletal pain conditions: Use of brain imaging and machine learning;Boissoneault;Current Rheumatology Reports,2017

5. Statistics versus machine learning;Bzdok;Nature Methods,2018

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting Chronic Pain and Treatment Outcomes Using Machine Learning Models Based on High-dimensional Clinical Data From a Large Retrospective Cohort;Clinical Therapeutics;2024-06

2. Use of consumer wearables to monitor and predict pain in patients with sickle cell disease;Frontiers in Digital Health;2023-10-25

3. Classification of chronic pain using fMRI data: Unveiling brain activity patterns for diagnosis;Turkish Journal of Electrical Engineering and Computer Sciences;2023-10-07

4. Investigation of factors influencing low physical activity levels in community-dwelling older adults with chronic pain: a cross-sectional study;Scientific Reports;2023-08-28

5. Data Classification and Demand Prediction Methods Based on Semi-Supervised Agricultural Machinery Spare Parts Data;Agriculture;2022-12-23

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3