Prescriptions

AI Chatbot Answers for Drug Dosing Adjustments According to Renal Function in Geriatric Patients Using the New Scoring System (AI Quality Output Score): Cross-Sectional Study.

BACKGROUND: Preventable adverse drug reactions in geriatric patients are caused by overdosing, especially in cases of impaired renal function. Artificial intelligence (AI) chatbots are being discussed as tools to generate drug information, which can adjust drug dosing and prevent subsequent adverse drug reactions based on individualized patient data. However, the question arises as to the extent t...

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) is a global health burden characterized by heterogeneous progression trajectories. Without timely and appropriate management, CKD can lead to increased morbidity and mortality and a reduced quality of life. Therefore, early identification of patients at high risk of developing end-stage renal disease (ESRD) or mortality is essential to facilitate timely int...

Predicting ICU in-hospital mortality from text-encoded structured EHR data using adaptive transformer layer fusion.

Early identification of ICU patients at high mortality risk is essential for triage and timely intervention. We present adaptive layer fusion with int...

MAGC-DTI: modality-shared space and adaptive gated interactive cross-attention for drug-target interaction prediction.

Accurate drug-target interaction (DTI) prediction is crucial for drug repurposing and accelerating drug development. Although deep learning has advanc...

Academic early warning model based on machine learning and model application.

With the expansion of higher education, the uncertainty of students' academic completion and the diversity of academic crises have posed new challenge...

Label-free interferometry platform for drug response profiling of bioprinted tumor organoids at single-organoid resolution.

Organoids have become mainstay tools for drug discovery and personalized medicine. High-throughput imaging readouts for drug screening of tumor organo...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

Integrating artificial intelligence into drug delivery systems: Formulation development and current challenges.

Artificial intelligence (AI) is increasingly being explored as a supportive tool to address persistent challenges in drug delivery research, particula...

Geometric Structure-Aware Diffusion Model with Self-Optimization Strategy for Molecular Generation.

With the advancement of artificial intelligence, molecular design based on generative models offers novel approaches to accelerate drug discovery. How...

Development and validation of a machine learning-based clinical decision support tool for stratifying intravenous medication risk in hospitalized patients with heart failure.

INTRODUCTION: Hospitalized patients with heart failure (HF) frequently receive multiple high-risk intravenous (IV) medications, placing them at a subs...

Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities.

Tumor heterogeneity and drug resistance limit single-agent therapies, making combination treatments essential. However, traditional screening methods ...

Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.

The integration of multiomics technologies with artificial intelligence (AI) has become a transformative force in modern precision medicine, particula...

The relationship between AI self-efficacy and critical thinking among nursing students: A network analysis.

AIM: This study used network analysis to characterize the internal structure of artificial intelligence self-efficacy (AISE) among nursing students an...

Cross-study interpretable machine learning for prediction of NH3 and H2S emissions and identification of operational windows during composting.

Accurate prediction of NH3 and H2S emissions is essential for odor-risk control and process management during composting, but remains challenging beca...

Complex in vitro model developers' perspective on advanced hepatic in vitro culture methods for predictive drug safety.

INTRODUCTION: Adverse drug reactions remain a major barrier to drug development, with hepatotoxicity representing a persistent cause of clinical failu...

Beyond Molecular Structures: Investigating Demographic Factors in Drug-Induced Cardiotoxicity Prediction Models.

Predicting drug-induced cardiotoxicity remains one of the most important challenges in drug safety, contributing to a substantial share of clinical tr...

Learning Human-Environment Interactions via Wearable AI Interfaces.

Wearable artificial intelligence (AI) interfaces are reshaping the boundaries between humans and the environment. While prior works often focus on nar...

ProSiteHunter: A Unified Framework for Sequence-Based Prediction of Protein-Nucleic Acid and Protein-Protein Binding Sites.

Accurate identification of protein binding sites is essential for elucidating protein function, decoding molecular recognition, and guiding drug desig...

Global-Local Interaction and Recalibration Network for Salient Object Detection in Optical Remote Sensing Images.

Optical remote sensing images (RSIs) exhibit extensive spatial coverage and complex geographic backgrounds, where salient objects in the optical RSIs ...

From traditional classroom to AI-enhanced flipped classroom: a three-year pedagogical evolution for international students in pharmacology.

BACKGROUND: Pharmacology education faces challenges in developing higher-order thinking, especially for international students to overcome cross-cultu...