Addictions

Validation of an alcohol misuse classifier in hospitalized patients.

BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health record (EHR) may further augment the identification of alcohol misuse. Natural language processing (NLP) with supervised machine learning has been success...

Sensitivity Analysis and Extensions of Testing the Causal Direction of Dependence: A Rejoinder to Thoemmes (2019).

A commentary by Thoemmes on Wiedermann and Sebastian's introductory article on Direction Dependence Analysis (DDA) is responded to in the interest of elaborating and extending direction dependence principles to evaluate causal effect directionality. Considering Thoemmes' observation that some DDA principles are already well-established in machine learning, we argue that several other connections b...

Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence.

This paper presents a novel adaptive resonance theory (ART)-based modular architecture for unsupervised learning, namely the distributed dual vigilanc...

Nutritional, biochemical and microbiological composition of Mart. sap in Burkina Faso.

The palmyra palm Mart. grow wild and gives natural stands in several localities of central-eastern and eastern regions of Burkina Faso. This work aim...

Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine...

Machine-Learning-Based Detection of Craving for Gaming Using Multimodal Physiological Signals: Validation of Test-Retest Reliability for Practical Use.

Internet gaming disorder in adolescents and young adults has become an increasing public concern because of its high prevalence rate and potential ris...

Identifying cognitive deficits in cocaine dependence using standard tests and machine learning.

There is a growing need to address the variability in detecting cognitive deficits with standard tests in cocaine dependence (CD). The aim of the curr...

A newly developed transparent and flexible one-transistor memory device using advanced nanomaterials for medical and artificial intelligence applications.

 Artificial intelligence (AI) integrated circuits (IC) have memory devices as the key component. Due to more complex algorithms and architectures requ...

Computational Systems Pharmacology-Target Mapping for Fentanyl-Laced Cocaine Overdose.

The United States of America is fighting against one of its worst-ever drug crises. Over 900 people a week die from opioid- or heroin-related overdose...

Synthesis and Swelling Behavior of Sodium Alginate/Poly(vinyl alcohol) Hydrogels.

OBJECTIVES: Hydrogels are macromolecular networks able to absorb and release water/biological fluids in a reverse-phase manner, in response to specifi...

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most case...

Urban American Indian Adult Participation and Outcomes in Culturally Adapted and Mainstream Alcoholics Anonymous Meetings.

Very little is known about American Indian (AI) adults' participation in Alcoholics Anonymous (AA) despite their elevated rates of negative sequelae d...

A Radical Proposition: Opioid-sparing Prostatectomy.

Radical prostatectomy has largely become a procedure requiring a single day in the hospital with improving convalescence. Pre-operative counseling on ...

Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health re...

A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study.

BACKGROUND: Social media use is now ubiquitous, but the growth in social media communications has also made it a convenient digital platform for drug ...

Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty.

BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for ...

Physicochemical stability of nefopam and nefopam/droperidol solutions in polypropylene syringes for intensive care units.

INTRODUCTION: Nefopam has been reported to be effective in postoperative pain control with an opioid-sparing effect, but the use of nefopam can lead t...

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use c...

Salivary microRNAs identified by small RNA sequencing and machine learning as potential biomarkers of alcohol dependence.

Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). The miRNA transcriptome in the saliva of 56 African-Americans (AAs; 2...

Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China.

Water quality prediction is an effective method for managing and protecting water resources by providing an early warning against water quality deteri...