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Extraperitoneal Single-Port Robot-Assisted Radical Prostatectomy.

Robot-assisted radical prostatectomy (RARP) is currently the standard minimally invasive procedure f...

Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.

BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery...

Identifying risk of opioid use disorder for patients taking opioid medications with deep learning.

OBJECTIVE: The United States is experiencing an opioid epidemic. In recent years, there were more th...

Clinical Performance of a Gene-Based Machine Learning Classifier in Assessing Risk of Developing OUD in Subjects Taking Oral Opioids: A Prospective Observational Study.

OBJECTIVE: To reduce the incidence of Opioid Use Disorder (OUD), multiple guidelines recommend asses...

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 treat...

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...

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 ...

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 diagnosi...

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 th...

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 bo...

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 maintainin...

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 o...

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...

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 b...

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...

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 prescriptio...

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-inf...

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) techniqu...

What can the medical record reveal about problem opioid use?