Back Pain

Big data, artificial intelligence, and the opioid crisis.

Big data and predictive modelling for the opioid crisis: existing research and future potential.

A need exists to accurately estimate overdose risk and improve understanding of how to deliver treatments and interventions in people with opioid use disorder in a way that reduces such risk. We consider opportunities for predictive analytics and routinely collected administrative data to evaluate how overdose could be reduced among people with opioid use disorder. Specifically, we summarise globa...

Towards Equitable AI Interventions for People Who Use Drugs: Key Areas That Require Ethical Investment.

There has been growing investment in artificial intelligence (AI) interventions to combat the opioid-driven overdose epidemic plaguing North America. ...

Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.

OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to cr...

Development of a machine learning algorithm for early detection of opioid use disorder.

BACKGROUND: Opioid use disorder (OUD) affects an estimated 16 million people worldwide. The diagnosis of OUD is commonly delayed or missed altogether....

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better ind...

Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?

BACKGROUND: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used ...

Improved Classification of Medical Data Using Meta-Best Feature Selection.

Feature selection provides a useful method for reducing the size of large data sets while maintaining integrity, thereby improving the accuracy of neu...

An Automated Algorithm Incorporating Poincaré Analysis Can Quantify the Severity of Opioid-Induced Ataxic Breathing.

BACKGROUND: Opioid-induced respiratory depression (OIRD) is traditionally recognized by assessment of respiratory rate, arterial oxygen saturation, en...

Identifying opioid misuse among adolescents: Is the answer hiding in plain sight?

Labor Epidural Analgesia: Comparison of Two Different Intermittent Bolus Regimes.

BACKGROUND: Optimal labor analgesia can be provided with epidural by addition of opioid to the local anesthetic.

Investigation of Mean Platelet Volume and Platelet Count in the Blood of Patients with Lumbago and Sciatica.

BACKGROUND: Mean platelet volume (MPV) is a measurement defining the mean size of platelets in the blood. There has been no previous study of MPV and ...

Enhancing Risk Assessment in Patients Receiving Chronic Opioid Analgesic Therapy Using Natural Language Processing.

OBJECTIVES: Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to...

Prescription Opioid Dependence in Western New York: Using Data Analytics to Find an Answer to the Opioid Epidemic.

Opioid dependence and overdose is on the rise. One indicator is the increasing trends of prescription buprenorphine use among patient on chronic pain ...

Comparison of Intravitreal Bevacizumab and Intravitreal Diclofenac in the Treatment of Diabetic Macular Edema: a 6-month Follow-up.

The aim of this study was to compare the effect of intravitreal diclofenac, a non-steroidal anti-inflammatory drug (NSAID), with that of bevacizumab, ...

The prevalence of problem opioid use in patients receiving chronic opioid therapy: computer-assisted review of electronic health record clinical notes.

To estimate the prevalence of problem opioid use, we used natural language processing (NLP) techniques to identify clinical notes containing text indi...

What can the medical record reveal about problem opioid use?

Analysis of Drug Design for a Selection of G Protein-Coupled Neuro- Receptors Using Neural Network Techniques.

A study is presented on how well possible drug-molecules can be predicted with respect to their function and binding to a selection of neuro-receptors...