Addictions

Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach.

BACKGROUND: In recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult to classify as intentional or unintentional. Intentional overdose is difficult to detect, partially due to the lack of predictors and social stigmas t...

Training confounder-free deep learning models for medical applications.

The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variables (e.g., diagnosis). Improper modeling of those relationships often results in spurious and biased associations. Traditional machine learning and st...

A generalized machine-learning aided method for targeted identification of industrial enzymes from metagenome: A xylanase temperature dependence case study.

Growing industrial utilization of enzymes and the increasing availability of metagenomic data highlight the demand for effective methods of targeted i...

Plasma Concentrations of Pro-inflammatory Cytokine IL-6 and Antiinflammatory Cytokine IL-10 in Short- and Long-term Opioid Users with Noncancer Pain.

INTRODUCTION: Little is known whether the duration of opioid use influences the concentrations of pro- and anti-inflammatory cytokines.

Host variables confound gut microbiota studies of human disease.

Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify ca...

Analysis of 17 fentanyls in plasma and blood by UPLC-MS/MS with interpretation of findings in surgical and postmortem casework.

The opioid crisis is linked to an increased misuse of fentanyl as well as fentanyl analogs that originate from the illicit drug market. Much of our cu...

The use of machine learning improves the assessment of drug-induced driving behaviour.

RATIONALE: Car-driving performance is negatively affected by the intake of alcohol, tranquillizers, sedatives and sleep deprivation. Although several ...

Discrimination of alcohol dependence based on the convolutional neural network.

In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used fo...

A comparison of the effects and usability of two exoskeletal robots with and without robotic actuation for upper extremity rehabilitation among patients with stroke: a single-blinded randomised controlled pilot study.

BACKGROUND: Robotic rehabilitation of stroke survivors with upper extremity dysfunction may yield different outcomes depending on the robot type. Cons...

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification ...

Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, ...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the development and scale-up of novel AI interventions to aid i...

Data enhanced Hammett-equation: reaction barriers in chemical space.

It is intriguing how the Hammett equation enables control of chemical reactivity throughout chemical space by separating the effect of substituents fr...

Cryostructuring of Polymeric Systems : Application of Deep Neural Networks for the Classification of Structural Features Peculiar to Macroporous Poly(vinyl alcohol) Cryogels Prepared without and with the Additives of Chaotropes or Kosmotropes.

Macroporous poly(vinyl alcohol) cryogels (PVACGs) are physical gels formed via cryogenic processing of polymer solutions. The properties of PVACGs dep...

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stro...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alc...

Development of a High-Fidelity Robot-Assisted Kidney Transplant Simulation Platform Using Three-Dimensional Printing and Hydrogel Casting Technologies.

Despite the adoption of robotic donor nephrectomy, the steep learning curve of robotic recipient transplantation has hindered the implementation of a...

Investigation of MDMA Inhibitory Effect on CytochromeP450 3A4 in Isolated Perfused Rat Liver Model Using Tramadol.

MDMA (methylenedioxymethamphetamine) is a synthetic compound, which is a structurally derivative of amphetamine. Also, it acts like an amphetamine, s...

High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.

Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intra...

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential application...