AIMC Topic: Chronic Pain
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Exploring the Effect of an 8-Week AI-Composed Exercise Program on Pain Intensity and Well-Being in Patients With Spinal Pain: Retrospective Cohort Analysis.
JMIR formative research
Feb 18, 2025
BACKGROUND: Spinal pain, one of the most common musculoskeletal disorders (MSDs), significantly impacts the quality of life due to chronic pain and disability. Physical activity has shown promise in managing spinal pain, although optimizing adherence...
Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.
International journal of medical sciences
Jan 1, 2025
Antiepileptics and antidepressants are frequently prescribed for chronic pain, but their efficacy and potential adverse effects raise concerns, including dependency issues. Increased prescriptions, sometimes fraudulent, prompted reclassification of ...
Use of machine learning to identify prognostic variables for outcomes in chronic low back pain treatment: a retrospective analysis.
The Journal of manual & manipulative therapy
Nov 14, 2024
OBJECTIVES: Most patients seen in physical therapy (PT) clinics for low back pain (LBP) are treated for chronic low back pain (CLBP), yet PT interventions suggest minimal effectiveness. The Cochrane Back Review Group proposed 'Holy Grail' questions, ...
Moving towards the use of artificial intelligence in pain management.
European journal of pain (London, England)
Nov 10, 2024
BACKGROUND AND OBJECTIVE: While the development of artificial intelligence (AI) technologies in medicine has been significant, their application to acute and chronic pain management has not been well characterized. This systematic review aims to prov...
Predicting frailty in older patients with chronic pain using explainable machine learning: A cross-sectional study.
Geriatric nursing (New York, N.Y.)
Nov 8, 2024
Frailty is common among older adults with chronic pain, and early identification is crucial in preventing adverse outcomes like falls, disability, and dementia. However, effective tools for identifying frailty in this population remain limited. This ...
Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum.
Neurochemistry international
Oct 23, 2024
Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pa...
Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.
Pain
Oct 11, 2024
Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, experiencing more severe pain, and suffering greater pain-related disability. However, SEP is a multidimensional construct; there is a dearth of research...
Transforming personalized chronic pain management with artificial intelligence: A commentary on the current landscape and future directions.
Experimental neurology
Sep 29, 2024
Artificial intelligence (AI) has the potential to revolutionize chronic pain management by guiding the development of effective treatment strategies that are tailored to individual patient needs. This potential comes from AI's ability to analyze larg...
Unraveling the physiological and psychosocial signatures of pain by machine learning.
Med (New York, N.Y.)
Aug 7, 2024
BACKGROUND: Pain is a complex subjective experience, strongly impacting health and quality of life. Despite many attempts to find effective solutions, present treatments are generic, often unsuccessful, and present significant side effects. Designing...
Optimizing pain management in breast cancer care: Utilizing 'All of Us' data and deep learning to identify patients at elevated risk for chronic pain.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Jul 26, 2024
PURPOSE: The aim of the study was to develop a prediction model using deep learning approach to identify breast cancer patients at high risk for chronic pain.
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