Pain Management

Crocin exerts improving effects on indomethacin-induced small intestinal ulcer by antioxidant, anti-inflammatory and anti-apoptotic mechanisms.

Crocin is a plant-derived carotenoid and bears potent antioxidant property. Ranitidine (a histamine H receptor blocker) is used for peptic ulcer treatment. The present study was planned to investigate the effects of crocin and ranitidine on indomethacin-induced ulcer in small intestine of rats. Animals were randomized into two major groups including indo-methacin (10.00 mg kg, ulcer group, 48 rats...

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.

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 control is obtaining objective pain assessment when direct communication is lacking. For years, computer scientists have developed many different facial...

Epidemiological pathology of Aβ deposition in the ageing brain in CFAS: addition of multiple Aβ-derived measures does not improve dementia assessment using logistic regression and machine learning approaches.

Aβ-amyloid deposition is a key feature of Alzheimer's disease, but Consortium to Establish a Registry for Alzheimer's Disease (CERAD) assessment, base...

Machine learning: assessing neurovascular signals in the prefrontal cortex with non-invasive bimodal electro-optical neuroimaging in opiate addiction.

Chronic and recurrent opiate use injuries brain tissue and cause serious pathophysiological changes in hemodynamic and subsequent inflammatory respons...

A fluoroscopic assessment of brachial plexus block by the supraclavicular approach: Have we been overmedicating?

BACKGROUND: Ultrasonography-guided supraclavicular brachial plexus block has demonstrated safety as compared with landmark or nerve stimulation techni...

Subgrouping Factors Influencing Migraine Intensity in Women: A Semi-automatic Methodology Based on Machine Learning and Information Geometry.

BACKGROUND: Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of popu...

How people with dementia perceive a therapeutic robot called PARO in relation to their pain and mood: A qualitative study.

BACKGROUND: Interacting with social robots, such as the robotic seal PARO, has been shown to improve mood and acute pain for people with dementia. Lit...

Estimation of Bladder Pressure and Volume from the Neural Activity of Lumbosacral Dorsal Horn Using a Long-Short-Term-Memory-based Deep Neural Network.

In this paper, we propose a deep recurrent neural network (DRNN) for the estimation of bladder pressure and volume from neural activity recorded direc...

Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture.

A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroence...

Comparison of bupivacaine alone and in a combination with lidocaine for caudal block in patients undergoing circumcision: A historical cohort study.

OBJECTIVE: Optimal analgesia following ambulatory surgery is an important matter in patient satisfaction, and it reduces unnecessary hospital admissio...

Efficacy of Dexmedetomidine as an Adjuvant to Bupivacaine in Ultrasound-Guided Transverse Abdominis plane Block for Laparoscopic appendicectomy: A Randomised Controlled Study.

OBJECTIVE: Dexmedetomidine is an alpha 2-adrenergic agonist that prolongs analgesia as an adjuvant when added in neuraxial and peripheral nerve blocks...

An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenera...

Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model.

The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e...

Using machine learning to predict opioid misuse among U.S. adolescents.

This study evaluated prediction performance of three different machine learning (ML) techniques in predicting opioid misuse among U.S. adolescents. Da...

Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter.

IMPORTANCE: Automatic curation of consumer-generated, opioid-related social media big data may enable real-time monitoring of the opioid epidemic in t...

Few-shot hypercolumn-based mitochondria segmentation in cardiac and outer hair cells in focused ion beam-scanning electron microscopy (FIB-SEM) data.

We present a novel AI-based approach to the few-shot automated segmentation of mitochondria in large-scale electron microscopy images. Our framework l...

Antibiotic therapy in patients with high prostate-specific antigen: Is it worth considering? A systematic review.

: To address the question of whether antibiotic therapy can obviate the need for prostate biopsy (PBx) in patients presenting with high prostate-speci...

LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock.

Sepsis is a major health concern with global estimates of 31.5 million cases per year. Case fatality rates are still unacceptably high, and early dete...

Physicochemical stability of an admixture of lidocaine and ketamine in polypropylene syringe used in opioid-free anaesthesia.

OBJECTIVES: Opioid-free anaesthesia is a treatment strategy of pain management based on the use of drugs such as lidocaine, ketamine and dexmedetomidi...

Exploring Deep Physiological Models for Nociceptive Pain Recognition.

Standard feature engineering involves manually designing measurable descriptors based on some expert knowledge in the domain of application, followed ...