Prescriptions

Personalized machine learning prediction of next-day migraine persistence using digital headache diary data.

OBJECTIVES/BACKGROUND: Migraine is a disabling neurological disorder with substantial interindividual variability. Predicting whether an ongoing migraine attack will persist into the following day remains challenging. We evaluated the feasibility and predictive performance of personalized machine learning models for predicting next-day migraine persistence using longitudinal digital headache diary...

Leveraging artificial intelligence for workload balancing in information technology departments: A qualitative interpretive study.

BackgroundUneven distribution of workload, unequal task sharing, and inefficient resource utilization in information technology (IT) departments can negatively impact operational performance. Traditional and manual methods are unable to respond quickly and effectively to dynamic workload changes.ObjectiveThis study aims to examine the leverage effect of artificial intelligence in workload balancin...

Assessing the readability of AI-generated medication counseling for common Medicaid drug classes: metformin, lisinopril, and atorvastatin.

BACKGROUND: Metformin, lisinopril, and atorvastatin rank among the most commonly prescribed medications for Medicaid patients; however, patients often...

Automated comet assay analysis using YOLOv5-based deep learning.

BackgroundThe comet assay is a sensitive and widely used technique for assessing DNA damage at the single-cell level. Despite its advantages, traditio...

Dual AI models for gamma knife radiosurgery in craniopharyngioma: prescription dose modeling and outcome risk prediction.

BACKGROUND: Gamma Knife radiosurgery (GKRS) is an established adjunct for residual or recurrent craniopharyngioma, yet prescription dose selection rem...

Augmenting Medical Judgment in Signal Confirmation: Design Considerations for an AI-Enabled Causality Assessment Framework.

The safety signal assessment process evaluates the potential causal association between a medicinal product and a specific adverse event by integratin...

GATESynergy: Integrating Molecular Global-Local Aggregator and Hierarchical Gene-Gated Encoder for Drug Synergy Prediction.

Combination drug therapy is an effective approach to combating drug resistance and enhancing therapeutic efficacy in complex diseases such as cancer. ...

Determinants of modern family planning use among married adolescents in Bangladesh: evidence from a machine learning approach.

BACKGROUND: Modern family planning (FP) is essential for improving the reproductive health of adolescent women, especially in Bangladesh, where early ...

An AI-Assisted pictorial measure of children's dental anxiety during the initial child-dentist interaction.

BACKGROUND: The potential influence of the initial child-dentist interaction on dental anxiety (DA) in preschool children remains insufficiently under...

Transcranial photobiomodulation improves prefrontal oxygenation and impulse control in adults with ADHD: a randomized controlled trial.

BACKGROUND: Impulsivity in individuals with attention-deficit/hyperactivity disorder (ADHD) diminishes quality of life. Cortical hypometabolism has be...

Beyond transparency: why Traditional Chinese Medicine (TCM) need explainable artificial intelligence (XAI).

The integration of artificial intelligence (AI) with Traditional Chinese Medicine (TCM) is rapidly expanding, creating new opportunities for digital d...

Machine Learning for RNA-Targeting Drug Design.

Targeting RNA with small molecules offers significant therapeutic potential. Machine learning could substantially accelerate preclinical drug discover...

Synergistic Decoupling of Distance and Velocity in a Triboelectric Touchless Sensor for Intelligent Identity Recognition.

Touchless identity recognition is a crucial direction for future human-computer interaction, with broad application potential particularly in healthca...

Nonverbal AI-Based Communication Robot for Staff in Disaster-Affected Care Facilities: Exploratory ABAB Intervention Study.

BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent tor...

Metabolomic signatures for diagnosis and clinical severity in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) remains challenging to diagnose at early stages owing to subtle and heterogeneous clinical manifestations and the...

Bayesian Uncertainty-Guided Fidelity Fusion for Bioactivity Prediction.

Accurate prediction of molecular bioactivity is a fundamental goal in rational drug design but remains challenging due to data scarcity and label imba...

VITAGRAPH: building a knowledge graph for biologically relevant learning tasks.

The complexity of human biology poses ongoing challenges, driving global interdisciplinary research. Artificial intelligence has become a powerful too...

Automated quantification of drug-induced cell death via vacuolation scoring in microscopic images.

Cell death plays a critical role in maintaining cellular homeostasis. The accurate evaluation of cell death is essential to determine the efficacy of ...

Medical Affairs in the Age of Complexity: From Scientific Support to Strategic Enterprise Integrator.

Regulatory acceleration, expanded reliance on real-world evidence (RWE), and increasing integration of artificial intelligence (AI) into healthcare sy...

ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms.

Predicting cancer drug responses (CDRs) accurately remains a significant challenge due to the complexity of tumor biology and the limitations of exist...