Addictions

Impact of COVID-19-related data drift on machine-learning prognostic models predicting 30-day opioid-related emergency department visits, hospitalisation or mortality: a population-level administrative data study in Alberta, Canada.

OBJECTIVE: To develop machine-learning (ML) models during the COVID-19 pandemic and adjacent time periods to evaluate the impact of data drift on model performance. DESIGN: This prognostic study used population-level administrative health data to develop ML prediction models. SETTING: Alberta, Canada during 2019-2023. PARTICIPANTS: All patients over 18 who received at least one opioid dispensation...

Altered EEG markers of reward learning during abstinence in alcohol dependence: A probabilistic reversal learning study.

OBJECTIVE: This study investigated neurophysiological and behavioural adaptations in reward learning and decision making which may contribute to the development and persistence of alcohol use disorder. METHODS: 20 abstinent alcohol dependent participants (mean abstinence: 20 months, range 1-76) and 26 healthy controls completed an electroencephalography (EEG) probabilistic reversal learning paradi...

An explainable machine learning framework for analyzing and predicting mental health problems among university students in Bangladesh.

Mental health problems (MHPs) among university students are an increasing public health concern globally, including in Bangladesh. While machine learn...

Development, Feasibility, Acceptability, and Usability of an Artificial Intelligence-Powered Chatbot (Suzy) to Support Patients in Substance Use Disorder Recovery: Multiphase Study.

BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, r...

Machine Learning Prediction Model for Dyslipidemia and Its Association With Atherothrombotic Events in 3 Independent Cohorts From South Korea, Japan, and the United Kingdom: Algorithm Development and Validation Study.

BACKGROUND: Dyslipidemia is a multifactorial and complex condition that warrants investigation through advanced analytical approaches such as machine ...

Connected parents, connected children: the relationship of smartphone, social media, and AI with parenting and children's tech consumption in Türkiye.

BACKGROUND: The objective of this study is to investigate parental utilization of smartphones, engagement with social media, and adoption of artificia...

Chatbot relational dependence and psychosis risk: Conversational artificial intelligence as a potential behavioral addiction context.

Conversational artificial intelligence (AI) chatbots are increasingly used for emotional support, companionship, and psychological reflection. Their c...

SPIRAL: A probabilistic deep learning framework for Chinese liquor (Baijiu) classification via near-infrared hyperspectral imaging.

Chinese liquor (Baijiu) is a complex alcoholic beverage whose chemical composition determines its alcohol content, aroma type, and brand. Accurate ide...

Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort.

BACKGROUND: Early prediction of depressive and anxiety disorders is challenging due to substantial heterogeneity in risk pathways. Conventional machin...

HIV and Substance Use Reduction for Youth Experiencing Homelessness: Development and Usability Study.

BACKGROUND: Youth experiencing homelessness face heightened vulnerability to HIV infection and substance use due to complex structural, psychosocial, ...

Machine learning using PROFUND components for 30-day readmission prediction in multimorbid patients: a prospective multicentre study.

Early hospital readmission in multimorbid patients remains a major clinical challenge. Although risk stratification tools are widely used, predictive ...

Prediction of postoperative desaturation and bradycardia in neonates undergoing laparoscopic inguinal hernia repair: a retrospective cohort study.

BACKGROUND: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postopera...

Metabolic, demographic, and behavioral risk factors predict brain structural variability in the general population: an analysis of the human connectome project young adults.

BACKGROUND: Understanding whether commonly available metabolic, demographic, and behavioral factors can explain variability in brain structure may sup...

AI for Relational Reconnection and Social Support in Alzheimer's Disease: A Conceptual Framework for Socially Embedded Systems.

Alzheimer's Disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques ...

Dissecting the pathobiology of suspected sepsis through a comparative analysis of endothelial inflammatory and clinical prediction models.

Sepsis remains a formidable challenge in critical care, and is characterized by profound circulatory and cellular abnormalities driven by both systemi...

Reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.

The authors respond to reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.

Spatial concordance metrics and related risk factors of brain-peripheral barrier axes: unveiling distinct concordance patterns for mental and neurological axes.

Numerous studies have documented bidirectional interactions between the central nervous system and barrier organs (skin, gut, and lung). While genome-...

Clinical and quality of life predictors in patients with schizophrenia with and without substance use disorder.

The comorbidity of schizophrenia (SZ) and substance use disorder (SUD), also known as dual schizophrenia (SZ+), represents a clinical challenge due to...

Risk classification of oral potentially malignant disorders (OPMDs) using explainable machine learning through a community-based cross-sectional study in rural India.

BACKGROUND: Oral cancer is a major public health problem among the population of India. In rural setting whereby there is exposure to high-risk factor...