Prescriptions

Examining Increased Ritalin and Adderall Use Among Low-Income People Who Use Drugs: Mixed Methods Study.

BACKGROUND: Popular discourse often frames prescription stimulants Ritalin and Adderall as drugs for teens and emerging adults with greater financial resources (eg, students or young professionals), while illicit stimulants such as crack or methamphetamine are often considered drugs for older adults with lower incomes. Crack and methamphetamine are also frequently used in combination with opioids ...

Multimodality, interaction modeling, and multimodule architectures in genomic prediction: A unified conceptual framework.

The rapid expansion of genomic, environmental, phenomic, and other high-dimensional data sources has transformed genomic prediction in plant breeding. However, the terms multimodal, interaction modeling, and multimodule architecture are often used inconsistently, generating ambiguity regarding whether they refer to biological assumptions, data integration strategies, or computational design. These...

Large Language Models as Clinical Support Tools in Drug Information Services: Performance Comparison With Pharmacists.

BACKGROUND: Large language models (LLMs) are increasingly explored for drug information support, yet their reliability and clinical applicability rema...

Beam geometry optimization and convergence mode evaluation for knowledge-based planning of hippocampal avoidance whole-brain radiotherapy: A cross-platform study with quantitative scorecard assessment.

BACKGROUND: Hippocampal avoidance whole-brain radiotherapy (HA-WBRT) is used to treat brain metastases while preserving cognitive function by sparing ...

An informatics framework to harmonize electronic health record medication data for managed care analytics and artificial intelligence applications.

BACKGROUND: Artificial intelligence (AI) applications in managed care pharmacy depend on semantically consistent medication data, yet heterogeneous me...

Navigating uncertainty matters: Evaluating large language models for drug-drug interaction identification.

BACKGROUND: Accurate detection of drug-drug interactions (DDIs) is a fundamental component of safe medication management. Traditional rule-based clini...

Artificial intelligence-enabled causal estimate of Medicare drug plan integration in cancer care: A doubly robust machine learning instrumental variable analysis.

BACKGROUND: Artificial intelligence (AI) methods are increasingly used to strengthen policy evaluation in managed care pharmacy. Among Medicare benefi...

Artificial intelligence in prior authorization and coverage decisions: A systematic review of methods, evidence gaps, and future implications for patient access.

BACKGROUND: Prior authorization (PA) is intended to support appropriate use and spending of services and medications, yet 1 in 6 insured adults report...

Unsupervised Ensemble Learning for Active Drug-Induced Liver Injury Surveillance: Integrating Pharmacokinetic Burden With Enzyme Trajectories.

PURPOSE: Traditional drug-induced liver injury (DILI) surveillance relying on static laboratory thresholds frequently misses early kinetic evolution. ...

Multi-modal direct LINAC parameter prediction for pancreatic VMAT: An optimization-free approach.

BACKGROUND: Pancreatic cancer Volumetric Modulated Arc Therapy (VMAT) planning presents a significant dosimetric challenge due to the high-dose gradie...

Pain in laboratory fishes: What we know and what we need to know.

The scientific exploration of the capacity of fishes to experience pain has grown since the first identification of nociceptors in rainbow trout in 20...

PCIM-DTA: Pairwise Conditional Interaction Modeling for Drug-Target Affinity Prediction under Cold-Start Scenarios.

MOTIVATION: Cold-start drug-target affinity prediction remains challenging because static interaction mechanisms cannot adapt to individual drug-targe...

When an Algorithm Renews a Prescription.

Affective Generative Artificial Intelligence Use and Youth Mental Health.

IMPORTANCE: Adolescents are increasingly using generative artificial intelligence (AI) as an anonymous emotional support system, yet the association b...

Advances in the emerging field of epi-informatics in drug discovery: roads taken and future prospects.

INTRODUCTION: Epigenetic drug discovery remains a promising drug discovery strategy that has long been driven by advances in computational approaches....

Development of a machine-learning risk stratification tool for vasoactive medication need after two-bolus fluid resuscitation in pediatric suspected sepsis.

BACKGROUND: Timely vasopressor initiation is critical in fluid-refractory pediatric septic shock, yet clinicians lack objective tools to identify chil...

Personalized evaluation of NT-proBNP and clinical characteristics in suspected heart failure: the PRECISE-HF study.

BACKGROUND AND AIMS: N-terminal pro-B-type natriuretic peptide (NT-proBNP) is recommended to guide echocardiography referral in community-based patien...

Predictive Safety in the Era of Artificial Intelligence: Promises, Limits, and the Case for an Enterprise Lifecycle Evidence Ecosystem.

Drug safety remains central to patient benefit, as maximizing the value of beneficial therapies requires recognition, appropriate characterization, an...

MIDAS: A multimodal interview-based framework for depression assessment from clinical interviews.

Automated depression assessment from clinical interviews is a challenging intelligent healthcare task because depressive states are reflected not only...

Speech-based relapse prediction in psychosis using explainable AI: Protocol for the international multicentre observational TRUSTING study.

INTRODUCTION: The course of psychotic disorders typically involves relapses. Early warning signs vary between individuals and are difficult to detect ...