Addictions

Gray-Level Co-occurrence Matrix Analysis for the Detection of Discrete, Ethanol-Induced, Structural Changes in Cell Nuclei: An Artificial Intelligence Approach.

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational metho...

The Use of Machine Learning in MicroRNA Diagnostics: Current Perspectives.

MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation an...

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".

Extraperitoneal Single-Port Robot-Assisted Radical Prostatectomy.

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

Application of bi-modal signal in the classification and recognition of drug addiction degree based on machine learning.

Most studies on drug addiction degree are made based on statistical scales, addicts' account, and su...

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...

Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction.

Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-...

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 ...

Recombinant human thyrotropin thyroid hormone withdrawal in differentiated thyroid carcinoma follow-up: a single center experience.

INTRODUCTION: Our goal was to evaluate and compare the diagnostic utility of thyroid hormone withdra...

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...

Computational framework for detection of subtypes of neuropsychiatric disorders based on DTI-derived anatomical connectivity.

Many brain disorders - such as Alzheimer's disease, Parkinson's disease, schizophrenia and autism - ...

Multimodal Automatic Coding of Client Behavior in Motivational Interviewing.

Motivational Interviewing (MI) is defined as a collaborative conversation style that evokes the clie...

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...