Pain Management

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs.

The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus photographs was evaluated. A large database of fundus photographs (n = 14,822) from a racially and ethnically diverse group of individuals (over 33% of African descent) was evaluated by expert reviewers and classified as GON or healthy. Several deep learning architectures and the impact of transfer...

A computational strategy for finding novel targets and therapeutic compounds for opioid dependence.

Opioids are widely used for treating different types of pains, but overuse and abuse of prescription opioids have led to opioid epidemic in the United States. Besides analgesic effects, chronic use of opioid can also cause tolerance, dependence, and even addiction. Effective treatment of opioid addiction remains a big challenge today. Studies on addictive effects of opioids focus on striatum, a ma...

Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's di...

Intravenous Fluid for the Treatment of Emergency Department Patients With Migraine Headache: A Randomized Controlled Trial.

STUDY OBJECTIVE: The objective of this pilot study is to assess the feasibility and necessity of performing a large-scale trial to measure the effect ...

Feasibility and Acceptability of Mobile Phone-Based Auto-Personalized Physical Activity Recommendations for Chronic Pain Self-Management: Pilot Study on Adults.

BACKGROUND: Chronic pain is a globally prevalent condition. It is closely linked with psychological well-being, and it is often concomitant with anxie...

Identifying substance use risk based on deep neural networks and Instagram social media data.

Social media may provide new insight into our understanding of substance use and addiction. In this study, we developed a deep-learning method to auto...

Multimodal MRI-based classification of migraine: using deep learning convolutional neural network.

BACKGROUND: Recently, deep learning technologies have rapidly expanded into medical image analysis, including both disease detection and classificatio...

Utilizing soft constraints to enhance medical relation extraction from the history of present illness in electronic medical records.

Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous res...

Determining Pain Catastrophizing From Daily Pain App Assessment Data: Role of Computer-Based Classification.

This study compared persons with chronic pain who consistently reported that their pain was worsening with those who reported that their pain was impr...

The Elephant in the Room: Outbreak of Carfentanil Deaths in Minnesota and the Importance of Multiagency Collaboration.

Over a three-month period in early 2017, the Hennepin County Medical Examiner's Office investigated nine apparent opioid toxicity deaths that occurred...

Evaluation of analgesic efficacy of dexmedetomidine as adjuvant with ropivacaine in ultrasound-guided adductor canal block in patients following anterior cruciate ligament reconstruction surgeries.

INTRODUCTION: Local anaesthetic (LA) with highly selective alpha-2 agonist dexmedetomidine has not been evaluated in adductor canal block (ACB) for ar...

Small Intestinal Bacterial Overgrowth in Patients With Cirrhosis.

Small intestinal bacterial overgrowth (SIBO) is defined by increased density and/or abnormal composition of microbiota in the small bowel. SIBO is oft...

Wearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach.

Wearable sensors can provide detailed information on human movement but the clinical impact of this information remains limited. We propose a machine ...

A deep convolutional neural network approach for astrocyte detection.

Astrocytes are involved in various brain pathologies including trauma, stroke, neurodegenerative disorders such as Alzheimer's and Parkinson's disease...

Ethambutol-induced optic neuropathy in renal disorder: a clinico-electrophysiological study.

OBJECTIVE: To report the spectrum of ethambutol induced optic neuropathy in a group of renal patients with tuberculosis and the role of visual evoked ...

Twelve weeks of supervised exercise improves self-reported symptom burden and fatigue in chronic kidney disease: a secondary analysis of the 'ExTra CKD' trial.

BACKGROUND: Chronic kidney disease (CKD) patients experience a high symptom burden including fatigue, sleep difficulties, muscle weakness and pain. Th...

Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences.

Machine learning based predictions of protein⁻protein interactions (PPIs) could provide valuable insights into protein functions, disease occurrence, ...

Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection.

Purpose To determine the feasibility of using a deep learning approach to detect cartilage lesions (including cartilage softening, fibrillation, fissu...

Hybrid 3D/2D Convolutional Neural Network for Hemorrhage Evaluation on Head CT.

BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology for image recognition. This study evaluates a convolutional neural net...

RDE: A novel approach to improve the classification performance and expressivity of KDB.

Bayesian network classifiers (BNCs) have demonstrated competitive classification performance in a variety of real-world applications. A highly scalabl...