AIMC Topic: Pain Measurement

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Current state of science in machine learning methods for automatic infant pain evaluation using facial expression information: study protocol of a systematic review and meta-analysis.

BMJ open Dec 11, 2019
INTRODUCTION: Infants can experience pain similar to adults, and improperly controlled pain stimuli could have a long-term adverse impact on their cognitive and neurological function development. The biggest challenge of achieving good infant pain co...
Infant Pain Measurement Systematic Reviews as Topic Meta-Analysis as Topic Facial Expression Humans Machine Learning Research Design
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Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Jul 24, 2019
BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of repeat celiac plexus neurolysis and to build an artificial neural network model able to predict pain ...
Likelihood Functions Disease Progression Celiac Plexus Nerve Block Treatment Outcome Aged, 80 and over Humans Pain Pancreatic Neoplasms Adult Pain Management Machine Learning Predictive Value of Tests Male Endosonography Female Pain Measurement Middle Aged Aged
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Children's Fear and Pain During Medical Procedures: A Quality Improvement Study With a Humanoid Robot.

The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres Jul 18, 2019
BACKGROUND: Pediatric patients undergo a variety of painful medical procedures.
Robotics Pain Measurement Pain Quality Improvement Humans Child Fear
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Feasibility of a Real-Time Clinical Augmented Reality and Artificial Intelligence Framework for Pain Detection and Localization From the Brain.

Journal of medical Internet research Jun 28, 2019
BACKGROUND: For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical envir...
Spectroscopy, Near-Infrared Pain Measurement Augmented Reality Feasibility Studies Pain Humans Artificial Intelligence Brain Adult
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Diagnosis of pain in the right iliac fossa. A new diagnostic score based on Decision-Tree and Artificial Neural Network Methods.

Cirugia espanola Apr 18, 2019
INTRODUCTION: Pain in the right iliac fossa (RIF) continues to pose diagnostic challenges. The objective of this study is the development of a RIF pain diagnosis model based on classification trees of type CHAID (Chi-Square Automatic Interaction Dete...
Humans Neural Networks, Computer Female Male Abdominal Pain Middle Aged Ilium Inflammation Reproducibility of Results Decision Trees Adult Diagnosis, Differential Pain Measurement Appendicitis
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A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

Osteoarthritis and cartilage Apr 16, 2019
OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progressi...
Menisci, Tibial Congresses as Topic National Institutes of Health (U.S.) Biological Variation, Population Pain Measurement Osteoarthritis, Knee Collagen Type II Cartilage, Articular Databases, Factual Biomarkers Female Aged Disease Progression Severity of Illness Index United States Male Middle Aged Humans Machine Learning
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Diagnosing osteoarthritis from T maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort.

Osteoarthritis and cartilage Mar 21, 2019
OBJECTIVE: We aim to study to what extent conventional and deep-learning-based T relaxometry patterns are able to distinguish between knees with and without radiographic osteoarthritis (OA).
Humans Aged Sensitivity and Specificity Male Algorithms Female Cartilage, Articular Deep Learning Magnetic Resonance Imaging Middle Aged Pain Measurement Disease Progression Osteoarthritis, Knee Severity of Illness Index Case-Control Studies
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Application of an artificial neural network model for early outcome prediction of gamma knife radiosurgery in patients with trigeminal neuralgia and determining the relative importance of risk factors.

Clinical neurology and neurosurgery Feb 12, 2019
OBJECTIVES: Stereotactic radiosurgery (SRS) is a minimally invasive modality for the treatment of trigeminal neuralgia (TN). Outcome prediction of this modality is very important for proper case selection. The aim of this study was to create artifici...
Radiosurgery Trigeminal Neuralgia Kaplan-Meier Estimate Humans Predictive Value of Tests Adolescent Neural Networks, Computer Pain Measurement Treatment Outcome Prognosis Neurosurgical Procedures Diabetes Mellitus Radiation Dosage Female Male Risk Factors Middle Aged Aged Depression Aged, 80 and over Young Adult Adult Follow-Up Studies
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Study protocol for a randomised controlled trial of humanoid robot-based distraction for venipuncture pain in children.

BMJ open Dec 14, 2018
INTRODUCTION: Intravenous insertion (IVI) is a very common procedure in the emergency department (ED). IVI is often painful and stressful for both children and their families. Currently, distraction therapy is not used as a standard of care for IVI i...
Equivalence Trials as Topic Male Child Infusions, Intravenous Pain Management Robotics Humans Adaptation, Psychological Emergency Service, Hospital Female Phlebotomy Pain Measurement Alberta Hospitals, Pediatric Attention
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What does a pain 'biomarker' mean and can a machine be taught to measure pain?

Neuroscience letters Nov 29, 2018
Artificial intelligence allows machines to predict human faculties such as image and voice recognition. Can machines be taught to measure pain? We argue that the two fundamental requirements for a device with 'pain biomarker' capabilities are hardwar...
Pain Terminology as Topic Machine Learning Biomarkers Pain Measurement Electroencephalography
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