AIMC Topic: Pain Measurement

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Machine learning research methods to predict postoperative pain and opioid use: a narrative review.

Regional anesthesia and pain medicine
The use of machine learning to predict postoperative pain and opioid use has likely been catalyzed by the availability of complex patient-level data, computational and statistical advancements, the prevalence and impact of chronic postsurgical pain, ...

Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach.

JMIR formative research
BACKGROUND: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports o...

Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques.

Journal of shoulder and elbow surgery
BACKGROUND: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for sym...

Comparison between AI and human expert performance in acute pain assessment in sheep.

Scientific reports
This study explores the question whether Artificial Intelligence (AI) can outperform human experts in animal pain recognition using sheep as a case study. It uses a dataset of N = 48 sheep undergoing surgery with video recordings taken before (no pai...

Decoding of pain during heel lancing in human neonates with EEG signal and machine learning approach.

Scientific reports
Currently, pain assessment using electroencephalogram signals and machine learning methods in clinical studies is of great importance, especially for those who cannot express their pain. Since newborns are among the high-risk group and always experie...

Diagnosis of Pain Deception Using Minnesota Multiphasic Personality Inventory-2 Based on XGBoost Machine Learning Algorithm: A Single-Blinded Randomized Controlled Trial.

Medicina (Kaunas, Lithuania)
: Assessing pain deception is challenging due to its subjective nature. The main goal of this study was to evaluate the diagnostic value of pain deception using machine learning (ML) analysis with the Minnesota Multiphasic Personality Inventory-2 (MM...

Automated video-based pain recognition in cats using facial landmarks.

Scientific reports
Affective states are reflected in the facial expressions of all mammals. Facial behaviors linked to pain have attracted most of the attention so far in non-human animals, leading to the development of numerous instruments for evaluating pain through ...

Automated acute pain prediction in domestic goats using deep learning-based models on video-recordings.

Scientific reports
Facial expressions are essential in animal communication, and facial expression-based pain scales have been developed for different species. Automated pain recognition offers a valid alternative to manual annotation with growing evidence across speci...

Developing and Validating a Multimodal Dataset for Neonatal Pain Assessment to Improve AI Algorithms With Clinical Data.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses
BACKGROUND: Using Artificial Intelligence (AI) for neonatal pain assessment has great potential, but its effectiveness depends on accurate data labeling. Therefore, precise and reliable neonatal pain datasets are essential for managing neonatal pain.

Pain Assessment for Patients with Dementia and Communication Impairment: Feasibility Study of the Usage of Artificial Intelligence-Enabled Wearables.

Sensors (Basel, Switzerland)
BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with which to assess pain through the measurement of signals associated with physiologic responses to pain detected by wearables. We conducted a prospectiv...