Addictions

Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects.

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the impact of the pandemic suggest the potential for similar inequities for overdose. Our objective was to identify subgroups of New York State Medicaid enrollees who experienced the greatest increases in non-fatal opioid overdose risk following onset of ...

Prediction of Relapse Using Digital Technology in People in Recovery From Substance Use Disorders: Early Economic Evaluation With a Case Study of the Subreal App.

BACKGROUND: Many people relapse after achieving abstinence in substance use disorders. Health care providers may scan the horizon for new technologies to predict response that allow interventions to be targeted rather than routine. Currently, no such predictive technologies are available in the United Kingdom. The Subreal app is available for use in research contexts, but no clinical data specific...

Unlocking clinical narratives: how natural language processing and artificial intelligence can address data deficits and mitigate health inequities in urgent and emergency care.

The Urgent and Emergency Care system generates a wealth of clinical information, but our ability to harness this for public health planning and to add...

Content analysis of output from generative artificial intelligence chatbots when prompted about breast cancer and alcohol consumption.

OBJECTIVES: Alcohol is a group one carcinogen and contributes to breast cancer risk for women. Awareness of this relationship remains low. Generative ...

The impact of regional block presence on large language model-based postoperative analgesia recommendations in abdominal surgery: a comparative study using real-world patient data.

BACKGROUND: Postoperative pain management is a core component of anesthesiology practice, with regional anesthesia playing a key role in multimodal an...

Exposome-wide patterns predict brain health in aging.

Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference...

Radiomics-based feature exploration and auxiliary diagnostic model construction for gaming disorder.

Subjective biases in current clinical assessments create an urgent need for objective biomarkers in Gaming Disorder (GD). Radiomics could help in diag...

Subgroup identification of disparities in buprenorphine discontinuation in opioid-use disorder: A Virtual Twins machine learning approach using nationwide United States claims data, 2006-2022.

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This st...

High-Performance Transparent, Deformable, and Recoverable Biomimetic Stevia-PVA Hydrogel Triboelectric Nanogenerator with Machine Learning-Assisted Motion Recognition.

Rapid breakthroughs in IoT and AI have raised demand for portable, self-powered, flexible sensor devices. Hydrogels with high conductivity, mechanical...

Impact of multimodal information on the estimation of fetal growth indicators using machine learning regression models.

Accurate estimation of fetal growth indicators such as birth weight, birth length, and gestational age at birth is essential for monitoring pregnancy ...

AI-derived therapeutic development of a serotonin receptor-targeting drug for the treatment of opioid use disorder.

The opioid epidemic has led to a devastating loss of life nationwide. Of those dependent on opioids, many individuals desire to quit or reduce use, bu...

Explainable machine learning with SHAP decodes the heterogeneous burden of nasopharyngeal carcinoma in high-risk aging Asia.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a global public health concern, with a particularly high burden concentrated in East Asia, Southeast Asi...

Examining Ethnic and Racial Variations in Opioid-related Hospitalizations Using Western U.S. Electronic Health Records.

It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.

Large language models are rapidly becoming embedded in everyday life through artificial intelligence (AI) chatbots that people use for practical assis...

Dynamic EEG spectral changes during acute alcohol intoxication and propofol exposure: Implications for machine-learning-based alcoholism detection.

Bioinspired Leaky Integrate-and-Fire Neurons Enabled by Reconfigurable Hydrogel Memristors.

Biological leaky integrate-and-fire (LIF) neurons are dynamic, living computational systems that modulate signal strength via synaptic plasticity and ...

Machine Learning Approaches to Identify Physical, Psychological, and Social Predictors of Worsening Frailty Transitions Among Community-Dwelling Older Adults: A Longitudinal Cohort Study.

BACKGROUND: Frailty poses a significant challenge to aging societies, with increasing attention being paid to the concept of frailty transitions. Wors...

Generative AI Empower Addiction-Related Brain Circuits Detection via Graph Diffusion-Infused Adversarial Learning.

The study of the nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-relat...

Scalp Electroencephalography Markers of Hidden Interictal Epileptiform Discharges in the Mesial Temporal Lobe.

Interictal epileptiform discharges (IEDs) are crucial for epilepsy diagnosis but are often undetectable on scalp EEG (scEEG). This study aims to devel...

Comparative Performance of Artificial Intelligence-Based Computer-Aided Detection Systems for Colorectal Polyps: A Systematic Review and Network Meta-Analysis.

BACKGROUND AND AIMS: Computer-aided detection (CADe) is anticipated to enhance adenoma detection rate (ADRs). The aim of this study was to systematica...