Pain Management

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer's disease neuropathologies.

Deep neural networks (DNNs) capture complex relationships among variables, however, because they require copious samples, their potential has yet to be fully tapped for understanding relationships between gene expression and human phenotypes. Here we introduce an analysis framework, namely MD-AD (Multi-task Deep learning for Alzheimer's Disease neuropathology), which leverages an unexpected synerg...

A Combinatorial Deep Learning Structure for Precise Depth of Anesthesia Estimation From EEG Signals.

Electroencephalography (EEG) is commonly used to measure the depth of anesthesia (DOA) because EEG reflects surgical pain and state of the brain. However, precise and real-time estimation of DOA index for painful surgical operations is challenging due to problems such as postoperative complications and accidental awareness. To tackle these problems, we propose a new combinatorial deep learning str...

Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis.

BACKGROUND: Osteoporosis is an underdiagnosed and undertreated disease worldwide. Recent studies have highlighted the use of simple vertebral trabecul...

Predicting postoperative pain following root canal treatment by using artificial neural network evaluation.

This study aimed to evaluate the accuracy of back propagation (BP) artificial neural network model for predicting postoperative pain following root ca...

Losartan as a Steroid-Sparing Adjunct in a Patient With Features of Refractory Camurati-Engelmann Disease.

OBJECTIVE: The treatment of Camurati-Engelmann disease (CED) involves the use of glucocorticoids, analgesics, and bisphosphonates; experience with the...

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.

BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and i...

Quantifying changes over 1 year in motor and cognitive skill after transient ischemic attack (TIA) using robotics.

Recent work has highlighted that people who have had TIA may have abnormal motor and cognitive function. We aimed to quantify deficits in a cohort of ...

Systematic review of Pharmacogenomics Knowledgebase evidence for pharmacogenomic links to the dopamine reward pathway for heroin dependence.

Genetics play an important role in opioid use disorder (OUD); however, few specific gene variants have been identified. Therefore, there is a need to ...

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. ...

Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy.

Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting sem...

Predicting and characterizing a cancer dependency map of tumors with deep learning.

Genome-wide loss-of-function screens have revealed genes essential for cancer cell proliferation, called cancer dependencies. It remains challenging t...

Single- versus multi-port robotic partial nephrectomy: a comparative analysis of perioperative outcomes and analgesic requirements.

Evidence supporting the safe use of the single-port (SP) robot for partial nephrectomy is scarce. The purpose of this study was to compare perioperati...

Identifying resting state differences salient for resilience to chronic pain based on machine learning multivariate pattern analysis.

Studies have documented behavior differences between more versus less resilient adults with chronic pain (CP), but the presence and nature of underlyi...

Cardiac Magnetic Resonance Images Superresolution via Multichannel Residual Attention Networks.

The deep neural network has achieved good results in medical image superresolution. However, due to the medical equipment limitations and the complexi...

Intraoperative multimodal analgesic bundle containing dexmedetomidine and ketorolac may improve analgesia after robot-assisted prostatectomy in patients receiving rectus sheath blocks.

BACKGROUND: Minimally invasive robot-assisted laparoscopic radical prostatectomy (RALP) has replaced open prostatectomy. However, RALP does not reduce...

Spatially-Aware Context Neural Networks.

A variety of computer vision tasks benefit significantly from increasingly powerful deep convolutional neural networks. However, the inherently local ...

Future roles of artificial intelligence in early pain management of newborns.

The advent of increasingly sophisticated medical technology, surgical interventions, and supportive healthcare measures is raising survival probabilit...

Multimodal Machine Learning Using Visual Fields and Peripapillary Circular OCT Scans in Detection of Glaucomatous Optic Neuropathy.

PURPOSE: To develop and validate a multimodal artificial intelligence algorithm, FusionNet, using the pattern deviation probability plots from visual ...

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic ...

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions.

The article presents a research in the field of complex sensing, detection, and recovery of communications networks applications and hardware, in case...