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Key features associated with opioid misuse in chronic pain: A machine learning cross-sectional study

Opioid misuse remains a critical public health concern, associated with increased risk of overdose, ...

Machine Learning Prediction of Pharmacogenetic Test Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: A Retrospective Cohort Study

Opioids are a widely prescribed class of medication for pain management. However, they have variable...

Childhood Maltreatment and Risk for Illicit Substance Use: Evidence for Mid-Adolescence as a Sensitive Exposure Period

Childhood maltreatment is a well-established risk factor for substance misuse. However, it remains u...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evalu...

Enhancing Anterior Quadratus Lumborum Block Accuracy with Artificial Intelligence: A Segmentation Approach Evaluated by Dice Score Metrics

Anterior quadratus lumborum (QL) block is a regional anesthesia technique shown to provide both soma...

Characterize Disease Progression Subphenotypes in Real World Populations with Overweight and Obesity using a Graph-based Neural Network Framework

Obesity is a chronic, heterogeneous condition, with risks, trajectories, and treatment responses tha...

Comparing computable structured phenotype- versus large language model-identification of opioid use disorder using electronic health record data

Opioid use disorder (OUD) is common in emergency departments (EDs); identification via structured co...

Machine learning-driven prediction of opioid and stimulant-related drug overdose fatalities: Analysis of the potential fourth wave

Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of al...

Heterogeneous epigenetic variation converges on splicing dysregulation in opioid addiction

Disease heterogeneity presents a major challenge for genetic and epigenetic dissection of complex tr...

Implementation of an Opioid Use Disorder (OUD) Machine-Learning Phenotype in Real-Time for the ADAPT Project

Develop and deploy a real-time, EHR-integrated machine learning phenotype to identify emergency depa...

Machine learning augmented genome-wide meta-analysis of prescription opioid use in 860,000 individuals

Opioid analgesics are widely prescribed for pain, yet individuals vary markedly in their patterns of...

Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.

OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze admini...

Functional Brain Network Identification in Opioid Use Disorder Using Machine Learning Analysis of Resting-State fMRI BOLD Signals

Understanding the neurobiology of opioid use disorder (OUD) using resting-state functional magneti...

A Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product

Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine...

Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text.

Natural Language Processing can be used to identify opioid use disorder in patients from clinical te...

Erector Spinae Plane Block versus Transversus Abdominis Plane Block for Robotic Inguinal Hernia Repair: A Blinded, Active-Controlled, Randomized Trial.

BACKGROUND: Regional anesthetic nerve blocks are widely used in the treatment of pain after outpatie...

Identification of Subphenotypes of Opioid Use Disorder Using Unsupervised Machine Learning.

This paper aimed to detect the latent clusters of patients with opioid use disorder and to identify ...

Using Natural Language Processing of Clinical Notes to Predict Outcomes of Opioid Treatment Program.

Potential of natural language processing (NLP) in extracting patient's information from clinical not...

Editorial Commentary: Big Data and Machine Learning in Medicine.

Recent research using machine learning and data mining to determine predictors of prolonged opioid u...

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups.

OBJECTIVES: To assess fairness and bias of a previously validated machine learning opioid misuse cla...

Comment on: "Predictive factors for opioid-free management after robotic radical prostatectomy: the value of a single-port robotic platform".