AIMC Topic: Pain

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Machine learning approaches applied in spinal pain research.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology Sep 17, 2021
The purpose of this narrative review is to provide a critical reflection of how analytical machine learning approaches could provide the platform to harness variability of patient presentation to enhance clinical prediction. The review includes a sum...
Humans Machine Learning Muscle, Skeletal Pain
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Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

The journal of pain Aug 21, 2021
Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pai...
Algorithms Phenotype Treatment Outcome Humans Machine Learning Pain Measurement Electroencephalography Pain
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Comparison of Feature Extraction Methods for Physiological Signals for Heat-Based Pain Recognition.

Sensors (Basel, Switzerland) Jul 15, 2021
While even the most common definition of pain is under debate, pain assessment has remained the same for decades. But the paramount importance of precise pain management for successful healthcare has encouraged initiatives to improve the way pain is ...
Hot Temperature Humans Machine Learning Databases, Factual Pain Measurement Pain
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Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.

PloS one Jul 9, 2021
In current clinical settings, typically pain is measured by a patient's self-reported information. This subjective pain assessment results in suboptimal treatment plans, over-prescription of opioids, and drug-seeking behavior among patients. In the p...
Physiology Models, Theoretical Humans Generalization, Stimulus Pain Machine Learning Galvanic Skin Response Algorithms
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Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

American journal of physiology. Regulatory, integrative and comparative physiology Jun 16, 2021
An objective measure of pain remains an unmet need of people with chronic pain, estimated to be 1/3 of the adult population in the United States. The current gold standard to quantify pain is highly subjective, based upon self-reporting with numerica...
Young Adult Adult Male Machine Learning Female Reproducibility of Results Signal Processing, Computer-Assisted Skin Feasibility Studies Severity of Illness Index Predictive Value of Tests Pain Measurement Humans Pain Perception Pain Threshold Galvanic Skin Response Electrodiagnosis Pain Hot Temperature Sympathetic Nervous System
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Automatic vs. Human Recognition of Pain Intensity from Facial Expression on the X-ITE Pain Database.

Sensors (Basel, Switzerland) May 10, 2021
Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whethe...
Humans Neural Networks, Computer Pain Facial Expression Databases, Factual Pain Measurement
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Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

JMIR mHealth and uHealth May 5, 2021
BACKGROUND: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hosp...
Adult Middle Aged Pain Measurement Pain Galvanic Skin Response Aged Aged, 80 and over Young Adult Humans Machine Learning Algorithms
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Deep learning approach to predict pain progression in knee osteoarthritis.

Skeletal radiology Apr 9, 2021
OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting pain progression in subjects with or at risk of knee osteoarthritis (OA).
Humans Retrospective Studies Female Male Osteoarthritis, Knee Longitudinal Studies Middle Aged Knee Joint Disease Progression Pain Deep Learning
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Semi-automated tracking of pain in critical care patients using artificial intelligence: a retrospective observational study.

Scientific reports Mar 4, 2021
Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause adverse events, including poor survival rates; however, continuous pain evaluation is difficult. Vital signs have traditionally been considered ineffec...
Japan Critical Care Support Vector Machine Pain Measurement Pain Male Middle Aged Logistic Models Female Humans Aged Machine Learning Adult Artificial Intelligence Retrospective Studies Critical Illness
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Prioritizing Pain-Associated Targets with Machine Learning.

Biochemistry Feb 19, 2021
While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model ...
Pain Humans Drug Discovery Machine Learning Analgesics Drug Delivery Systems Models, Biological Drug Design
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