ADHD/ADD

Adherence Risk Stratification in Physiatry: A Multivariate Analysis of Factors in Community-Based Care Using Algorithmic Modeling Techniques

Missed appointments represent a double-edged sword in community health settings. Policies designed to retain patients and ensure continuity of care for vulnerable populations often mean that discharging patients is rare, even in cases of frequent no-shows. However, this retention strains healthcare resources, disrupts workflows, and exacerbates inequities in access to care. In physiatry (PM&R), wh...

Deep learning-based polygenic scores enhance generalizability of psychiatric disorders prediction

Polygenic scores (PGSs) have emerged as promising tools for predicting complex traits from genetic data, however, their predictive performance for psychiatric disorders remains limited and the added value of deep learning (DL) over linear models is underexplored. In this study, we compared our DL model, Genome-Local-Net (GLN), with the linear model bigstatsr in predicting five psychiatric disorder...

Lack of children in public medical imaging data points to growing age bias in biomedical AI

Artificial intelligence (AI) is rapidly transforming healthcare, but its benefits are not reaching all patients equally. Children remain overlooked wi...

A conversational artificial intelligence agent for medication reconciliation and review

Medication reconciliation, the process of creating an accurate medication list for a patient, is critical to patient safety and care quality but requi...

Early Warning Model for Patient Deterioration: A Machine Learning Approach for Nurse-Led Monitoring

The early recognition of clinical deterioration in hospital inpatients continues to be a major challenge in healthcare. In this work, we proposed an i...

Machine Learning for Paediatric Related Decision Support in Emergency Care – A UK and Ireland Network Survey Study of Emergency Staff

There is great potential for artificial Intelligence (AI) and machine learning (ML) to support decision making in emergency departments (ED), however ...

Quantifying new threats to health and biomedical literature integrity from rapidly scaled publications and problematic research

The last three years have seen an explosion in published manuscripts analysing open-access health datasets, in many cases presenting misleading or bio...

Managing Data Uncertainty and Machine Learning for Adult ADHD Classification Using Accelerometry: OBF-Psychiatric Case Study

This study aims to enhance our understanding of ADHD individuals through accelerometer analysis while developing a framework for managing data uncerta...

Sex-Specific Diagnostic Subtypes in Adolescents Hospitalized for Substance Use Disorders Revealed by Transformer-Based Clustering

Substance use disorders (SUD) are a leading cause of psychiatric hospitalization among adolescents, yet the underlying diagnostic profiles and comorbi...

Classification of familial and non-familial ADHD using auto-encoding network and binary hypothesis testing

Family history is one the most powerful risk factor for attention-deficit/hyperactivity disorder (ADHD), yet no study has tested whether multimodal Ma...

Serious Gaming and Eye-Tracking for the Screening, Monitoring, Diagnosis and Treatment of Neurodevelopmental Disorders in Children: A Systematic Literature Review

Neurological development between the ages of 3 to 11 is crucial to the shaping of infrastructural capabilities like the executive functions that enabl...

Evaluating Large Language Models for ADHD Education: A Comparative Study of ChatGPT-5, DeepSeek V3, and Grok 4

Children with attention-deficit/hyperactivity disorder (ADHD) often face barriers to participating in organized sports, particularly when physical edu...

Explainable machine learning on weighted connectivity networks across frequencies for outcome prediction in comatose patients

Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is critical for guiding therapeutic decisions and improvi...

Environmental Chemicals as Modifiers of the Association between Age and Ovarian Reserve

To evaluate whether the well-established age-related reduction in antral follicle counts (AFC) is greater among women with higher concentrations of en...

Mapping Neurochemical Signatures onto Brain Structure for Neurotransmitter-Informed Discrimination of Schizophrenia Patients from Healthy Controls

Schizophrenia (SCZ) is associated with widespread gray matter volume (GMV) reductions, yet the underlying mechanisms driving these alterations remain ...

Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea.

The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In...

Amphetamine use and Parkinson's disease: integration of artificial intelligence prediction, clinical corroboration, and mechanism of action analyses.

Parkinson's disease (PD) is an increasingly prevalent neurologic condition for which symptomatic, but not preventative, treatment is available. Drug r...

STARFormer: A Novel Spatio-Temporal Aggregation Reorganization Transformer of FMRI for Brain Disorder Diagnosis

Many existing methods that use functional magnetic resonance imaging (fMRI) classify brain disorders, such as autism spectrum disorder (ASD) and att...

SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction

Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early sepsis prediction and identification allow for timely ...

The Value of AI Advice: Personalized and Value-Maximizing AI Advisors Are Necessary to Reliably Benefit Experts and Organizations

Despite advances in AI's performance and interpretability, AI advisors can undermine experts' decisions and increase the time and effort experts mus...