AIMC Topic: Pain, Postoperative
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Development and validation of machine learning models for predicting post-cesarean pain and individualized pain management strategies: a multicenter study.
BMC anesthesiology
Apr 10, 2025
BACKGROUND: Effective management of postoperative pain remains a significant challenge in obstetric care due to the variability in pain perception and response influenced by physical, medical, and psychosocial factors. Current standardized pain manag...
Predicting high-risk factors for postoperative inadequate analgesia and adverse reactions in cesarean delivery surgery: a prospective study.
International journal of surgery (London, England)
Apr 3, 2025
BACKGROUND: Early identification of high-risk factors for inadequate analgesia and adverse reactions in obstetric patients is critical for improving outcomes. This study developed a machine learning model to predict these factors and optimize anesthe...
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 research methods to predict postoperative pain and opioid use: a narrative review.
Regional anesthesia and pain medicine
Feb 5, 2025
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
Jan 27, 2025
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...
A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.
Current pain and headache reports
Jan 23, 2025
PURPOSE OF REVIEW: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper,...
Machine learning-augmented interventions in perioperative care: a systematic review and meta-analysis.
British journal of anaesthesia
Sep 24, 2024
BACKGROUND: We lack evidence on the cumulative effectiveness of machine learning (ML)-driven interventions in perioperative settings. Therefore, we conducted a systematic review to appraise the evidence on the impact of ML-driven interventions on per...
Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach.
Anesthesia and analgesia
Sep 4, 2024
BACKGROUND: Persistent opioid use is a common occurrence after surgery and prolonged exposure to opioids may result in escalation and dependence. The objective of this study was to develop machine-learning-based predictive models for persistent opioi...
Exploring the Potential of a Smart Ring to Predict Postoperative Pain Outcomes in Orthopedic Surgery Patients.
Sensors (Basel, Switzerland)
Aug 3, 2024
Poor pain alleviation remains a problem following orthopedic surgery, leading to prolonged recovery time, increased morbidity, and prolonged opioid use after hospitalization. Wearable device data, collected during postsurgical recovery, may help amel...
Harnessing artificial intelligence for predicting and managing postoperative pain: a narrative literature review.
Current opinion in anaesthesiology
Jun 25, 2024
PURPOSE OF REVIEW: This review examines recent research on artificial intelligence focusing on machine learning (ML) models for predicting postoperative pain outcomes. We also identify technical, ethical, and practical hurdles that demand continued i...
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