Practice Management

Readability of AI-Generated Patient Visit Summaries in Orthopedic Surgery: Retrospective Analysis.

BACKGROUND: Patient visit summaries (PVS) are patient-facing documents intended to reinforce communication and promote patient education after clinical encounters. Despite national recommendations that patient education materials be written at or below a sixth-grade reading level, most orthopedic materials substantially exceed this threshold. Current visit summaries are also time-consuming to gene...

Multimodal Digital Therapeutics Enhanced by Task Design and AI for Attention-Deficit/Hyperactivity Disorder Core Symptoms and Executive Functions in Children and Adolescents: Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Digital therapeutics (DTx) show promise as nonpharmacological interventions, but the comparative efficacy of different DTx modalities remains unclear. OBJECTIVE: This network meta-analysis (NMA) compared 4 DTx modalities (single-task, cognitive-motor dual-task, AI-int...

Cerebellum-inspired neural network of supervised learning with tensor-based sparse coding for multi-class classification.

Under the Marr-Ito-Albus framework, the cerebellum performs supervised learning in Purkinje cells upon the unsupervised sparse representations generat...

Methods of Evaluating Large Language Model-Based Health Care Applications Used by Nonprofessionals: Protocol for a Scoping Review.

BACKGROUND: Large language models (LLMs) are increasingly used in health care by nonprofessionals (ie, individuals without formal training in health-r...

Real-world evidence on antibiotic use among privately insured beneficiaries in Saudi Arabia: a retrospective analysis of claims data.

OBJECTIVES: Inappropriate and broad-spectrum antibiotic use contributes to antimicrobial resistance (AMR) and higher healthcare costs. In Saudi Arabia...

Building a Natural Language Processing Augmented Information Support System to Enhance Supportive Care for Patients With Prostate Cancer and Families: User-Centered, Iterative Approach.

BACKGROUND: Patients with prostate cancer and their families face significant challenges during transitions from diagnosis to treatment and posttreatm...

Agentic AI-Assisted Coding Offers a Unique Opportunity to Instill Epistemic Grounding during Software Development.

The capabilities of AI-assisted coding are progressing at a breakneck speed. Chat-based vibe coding has evolved into fully fledged AI-assisted, agenti...

Leveraging Artificial Intelligence and Natural Language Processing in Legal Epidemiology Studies: Opportunities and Challenges.

Legal epidemiology - the study of how laws influence health outcomes - is an emerging field with potential to inform policy and improve public health....

Exploring patients' and public perspectives on an oral capsule for gastric submucosal delivery in Denmark and the USA: a mixed-methods study protocol.

INTRODUCTION: Oral capsules for gastric submucosal delivery represent a fundamentally new route of administration for biologics, which are currently l...

Intron retention in health and amyotrophic lateral sclerosis.

Intron retention (IR) is the molecular phenomenon by which introns, historically thought to represent non-coding 'junk', remain unspliced within pre-m...

Temporal Drivers of Opioid-Related ED Visits: An Ensemble Machine Learning Study With Consensus-Based Feature Attribution.

Identification of modifiable risk factors for prescription opioid use disorder (OUD)-related emergency department (ED) visits (ICD-10 F11.xx) is a cli...

Leveraging machine learning with real-world data for hypothesis generation by identifying exposomic predictors in Parkinson's disease among farmers.

BackgroundMachine learning offers new avenues for complementing traditional epidemiological approaches by analyzing routinely collected, population-ba...

Ethical Risks and Governance Directions of Conversational Artificial Intelligence in Nursing Triage and Patient Education: Shared Foundations and Contextual Differences.

AIM: To provide an early-stage integrative synthesis of shared and scenario-specific ethical risks of Conversational Artificial Intelligence in nursin...

Screening for diabetic retinopathy with artificial intelligence in a primary care setting: a comparative cost analysis.

OBJECTIVE: Cost analysis of autonomous artificial intelligence (AI)-based screening of diabetic retinopathy (DR) for adults with diabetes at a primary...

Heterogeneity in the association between antihypertensive medications and Alzheimer's disease and related dementias risk: A multidimensional machine learning analysis to inform drug repurposing.

BackgroundAlzheimer's disease and related dementias (ADRD) place an immense burden on patients, families, and health systems in the United States. Hyp...

Twelve quick tips for AI-assisted coding in science.

While AI coding tools have demonstrated potential to accelerate software development, their use in scientific computing raises critical questions abou...

Mapping National Governance of AI for Health: Protocol for a Global Scoping Review.

BACKGROUND: AI is rapidly transforming health systems, expanding from diagnostic imaging and predictive analytics to large language model-enabled clin...

A Community-in-the-Loop Approach to Smart Home Monitoring for Aging in Place: Mixed Methods Evaluation of a Co-Designed Prototype.

BACKGROUND: The population of adults aged 65 and older is rapidly increasing, while the availability of caregivers is declining. Smart homes that prov...

Non-coding RNAs as central regulators of phytohormone signaling in plant abiotic stress responses.

Plants are continuously exposed to a wide range of abiotic stresses, including drought, salinity, temperature extremes, nutrient deficiency, and heavy...

Prediction of heart arrhythmia onset in patients with ICD using machine learning algorithms.

PURPOSE: The current study uses machine learning algorithms to predict the onset of cardiac arrhythmia in patients with implantable cardioverter-defib...