AIMC Topic: Pain Measurement
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Automatic pain classification in older patients with hip fracture based on multimodal information fusion.
Scientific reports
Jul 1, 2025
Given the limitations of unimodal pain recognition approaches, this study aimed to develop a multimodal pain recognition system for older patients with hip fractures using multimodal information fusion. The proposed system employs ResNet-50 for facia...
Construction and validation of a pain facial expressions dataset for critically ill children.
Scientific reports
May 17, 2025
Automatic pain assessment for non-communicative children is in high demand. However, the availability of related training datasets remains limited. This study focuses on creating a large-scale dataset of pain facial expressions specifically for Chine...
Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation.
Journal of medical Internet research
Mar 31, 2025
BACKGROUND: Chronic pain, affecting more than 20% of the global population, has an enormous pernicious impact on individuals as well as economic ramifications at both the health and social levels. Accordingly, tools that enhance pain assessment can c...
Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.
JMIR medical informatics
Mar 28, 2025
BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide. The development and progression of chronic pain are unique to each individual due to the contribution of interacting biological, psychological, and ...
Physiological Sensor Modality Sensitivity Test for Pain Intensity Classification in Quantitative Sensory Testing.
Sensors (Basel, Switzerland)
Mar 26, 2025
Chronic pain is prevalent and disproportionately impacts adults with a lower quality of life. Although subjective self-reporting is the "gold standard" for pain assessment, tools are needed to objectively monitor and account for inter-individual diff...
A stacking ensemble machine learning model for predicting postoperative axial pain intensity in patients with degenerative cervical myelopathy.
Scientific reports
Mar 22, 2025
Machine learning (ML) has been extensively utilized to predict complications associated with various diseases. This study aimed to develop ML-based classifiers employing a stacking ensemble strategy to forecast the intensity of postoperative axial pa...
Machine learning predicts spinal cord stimulation surgery outcomes and reveals novel neural markers for chronic pain.
Scientific reports
Mar 18, 2025
Spinal cord stimulation (SCS) is a well-accepted therapy for refractory chronic pain. However, predicting responders remain a challenge due to a lack of objective pain biomarkers. The present study applies machine learning to predict which patients w...
The need for epistemic humility in AI-assisted pain assessment.
Medicine, health care, and philosophy
Mar 15, 2025
It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that pain is commonly understood as an individual and subjective experience. The process of measuring and diagnosing pain is often a fraught an...
Outcomes of lateral femoral cutaneous nerve decompression surgery in meralgia paraesthetica: assessment of pain, sensory deficits, and quality of life.
International orthopaedics
Mar 7, 2025
PURPOSE: Meralgia paraesthetica (MP) is a rare neuropathy of the lateral femoral cutaneous nerve (LFCN), characterized by thigh pain, paraesthesia, or sensory loss. When conservative treatments fail, surgical interventions such as neurolysis or neure...
Comparison of predictive models for knee pain and analysis of individual and physical activity variables using interpretable machine learning.
The Knee
Mar 4, 2025
BACKGROUND: Knee pain is associated with not only individual factors such as age and obesity but also physical activity factors such as occupational activities and exercise, which has a significant impact on the lives of adults and the elderly.
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