Addictions

BSN with Explicit Noise-Aware Constraint for Self-Supervised Low-Dose CT Denoising.

Although supervised deep learning methods have made significant advances in low-dose computed tomography (LDCT) image denoising, these approaches typically require pairs of low-dose and normal-dose CT images for training, which are often unavailable in clinical settings. Self-supervised deep learning (SSDL) has great potential to cast off the dependence on paired training datasets. However, existi...

Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos.

Concussions present a significant risk to athletes, with females exhibiting higher rates and prolonged recovery times than males. Current sideline concussion detection methods, such as the King-Devick test commonly used as a rapid screening tool designed to evaluate eye movement, attention, language, and cognitive processing abilities suffer from validity issues. This is especially true among youn...

The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.

BackgroundMachine learning (ML) algorithms may improve the prognosis for serious illnesses such as cancer, identifying patients who may benefit from e...

Integration of multiple coinflip devices for high-quality random sampling.

Artificial intelligence, scientific computing, and probabilistic computing use random sampling to approximate solutions to various problems, with larg...

A predictive model for electrospun based Polyvinyl alcohol (PVA) nanofibers diameter using an artificial neural network.

The aim of this work is to develop a predictive model for electrospun based polyvinyl alcohol (PVA) nanofiber diameter. Artificial Neural Network is e...

Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions.

Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challe...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

An explainable multi-task deep learning framework for crash severity prediction using multi-source data.

Traffic accidents pose significant global challenges, causing substantial injuries, fatalities, and economic losses. Current research predominantly fo...

Foam Sclerotherapy for Symptomatic Cysts in ADPKD, ADPLD and Solitary Cysts.

BACKGROUND: This medical center migrated from alcohol to sotradecol foam sclerotherapy (SFS) because of perceived improved efficacy in managing sympto...

Chronic intermittent alcohol yields sex-specific disruptions in cortical-striatal-limbic oscillations in rats.

BACKGROUND: There are significant sex differences in the causes and consequences of alcohol misuse, suggesting that sex-specific neurobiological mecha...

Should We Use Behavioural Predictions in Organ Allocation?

Medical predictions, for example, concerning a patient's likelihood of survival, can be used to efficiently allocate scarce resources. Predictions of ...

Artificial Intelligence and Stigma in Addiction Research: Insights From the HEALing Communities Study Coalition Meetings.

OBJECTIVES: This paper describes how artificial intelligence (AI) was used to analyze meeting minutes from community coalitions participating in the H...

Death One Hour After Terminal Extubation in Children: Validation of a Machine Learning Model to Predict Cardiac Death After Withdrawal of Life-Sustaining Treatment in a Multicenter Cohort, 2009-2021.

OBJECTIVES: In the PICU, predicting death within 1 hour after terminal extubation (TE) is valuable in augmenting family counseling and in identifying ...

Sentiment Analysis Using a Large Language Model-Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation.

BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixe...

Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are...

Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.

Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-su...

Fully Wearable Devices for Real-Time Health Monitoring and Multimodal Sensing in Nanomedicine Using Multiplexed Green Biofuels.

Fully wearable devices are crucial for real-time health monitoring, but existing devices often lack stable power, on-site signal processing, and multi...

Skin cancer segmentation and classification by implementing a hybrid FrCN-(U-NeT) technique with machine learning.

Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infect...

Development and Validation of a Lifestyle-Based 10-Year Risk Prediction Model of Colorectal Cancer for Early Stratification: Evidence from a Longitudinal Screening Cohort in China.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, with growing evidence linking risk to lifestyle and ...

Predictive modeling of hemoglobin refractive index using Gaussian process regression with interpretability through partial dependence plots.

Accurately predicting the refractive index of hemoglobin across various wavelengths and concentrations is critical for advancing optical diagnostic te...