Psychiatry

Addictions

Latest AI and machine learning research in addictions for healthcare professionals.

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CAS-Colon: A Comprehensive Colonoscopy Anatomical Segmentation Dataset for Artificial Intelligence Development.

Artificial intelligence (AI) holds immense potential to transform gastrointestinal endoscopy by redu...

A Deep Learning Model for Predicting the Cement Soil Deformation Modulus.

Cement, widely used for backfill grouting in shield tunnels, plays a crucial role in maintaining the...

Evaluation of Net Withdrawal Time and Colonoscopy Video Summarization Using Deep Learning Based Automated Temporal Video Segmentation.

Adequate withdrawal time is crucial in colonoscopy, as it is directly associated with polyp detectio...

Analysis of risk factors for DUI and DWI crashes considering the built environment.

The risk level of alcohol-involved traffic crashes is closely related to alcohol consumption. Howeve...

AI-Driven Discovery and Optimization of Positive Allosteric Modulators for NMDA Receptors: Potential Applications in Depression.

-Methyl-d-aspartate receptors (NMDARs) are extensively distributed throughout the central nervous sy...

Relative importance of socioecological domains to predicting opioid-involved mortality.

BACKGROUND: The opioid crisis in the United States is a complex issue with interconnected factors th...

Exploration on Bubble Entropy.

Bubble entropy is a recently proposed entropy metric. Having certain advantages over popular definit...

Exploring the Impact of Ambient Gas Property on the Signal of Laser-Induced Breakdown Spectroscopy with Neural Network.

Laser-induced breakdown spectroscopy (LIBS) has long been regarded as an ideal analytical technology...

Hijacked Brain in Modern Obesity: Cue, Habit, Addiction, Emotion, and Restraint as Targets for Personalized Digital Therapy and Electroceuticals.

The global obesity epidemic can no longer be explained by personal choice or caloric excess alone. M...

Stigmatizing Language in Large Language Models for Alcohol and Substance Use Disorders: A Multimodel Evaluation and Prompt Engineering Approach.

OBJECTIVES: Large language models (LLMs) are increasingly used in health care communication but can ...

An illustration of multi-class roc analysis for predicting internet addiction among university students.

The internet is one of the essential tools today, and its impact is particularly felt among universi...

Self-Disclosure and Social Support in a Web-Based Opioid Recovery Community: Machine Learning Analysis.

BACKGROUND: The opioid crisis remains a critical public health challenge, with opioid use disorder (...

Cottonseed-Derived Reusable Bio-Carbon Gel Ink for DIW Printing Soft Electronic Textiles.

Soft electronics textiles have garnered global attention for their wearability and promising applica...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesi...

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 tomogr...

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 prolong...

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 c...

Mitigating Opioid Dependence in Orthopaedic Surgery: Current Strategies and Future Directions.

The opioid crisis presents a significant burden to patients and healthcare systems. Orthopaedic surg...

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 ...

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 sign...

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 100,0...

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