Prescriptions

AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.

Artificial intelligence (AI) systems have been demonstrated to improve the accuracy of screening mammograms. Here this prospective, paired, noninferiority clinical trial evaluated whether AI could safely reduce workload by excluding low-risk exams from radiologist reading. Between March 2022 and January 2024, 31,301 women were included in the trial and underwent routine mammograms. Two reading str...

The visual nature of social interaction and its impact on overall mood judgments.

Humans can rapidly assess a crowd's overall mood, allowing socially adaptive behaviour. Prior work suggests that an interacting individual's emotional judgment is shaped by the facial expressions of their interaction partner. However, research has yet to systematically investigate how social interactions - and the visual cues signaling them - influence judgments of overall mood in naturalistic sce...

Utilization and Feasibility of a Wearable Device in Patients With Sedative Effects of Drugs: Protocol for a Prospective Observational Study for the Advanced Respiratory Monitoring Events in Drug Toxicity (ARM-ED) Study.

BACKGROUND: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other sedative drugs can cause respiratory depression a...

An entropy-initiated coupled-trait ODE framework for modeling longitudinal cohort dynamics.

This work introduces a minimal, information-theoretic dynamical framework for modeling longitudinal cohort data using an entropy-initiated system of c...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable m...

Neural network-driven user behavior forecasting and personalized recommendation in power marketing.

With the development of smart grids and the complexity of power marketing, accurately predicting users behavior and recommending suitable products to ...

Rapid detection of drug-resistant leukemia cell using an optofluidic chip and machine learning.

BACKGROUND: Rapid detection of drug-resistant leukemia played a crucial role in formulating appropriate treatment plans for patients and improving the...

Machine learning-assisted Zr-MOFFe@SECHA fluorescence and colorimetric dual-mode intelligent platform for sensitive LPS detection.

BACKGROUND: Lipopolysaccharide (LPS) is a crucial diagnosis biomarker for sepsis. Accurate and sensitive determination of LPS in real samples (human s...

A machine learning-based classification method for SynRM faults.

Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applications due to their high efficiency, magnet-free con...

BKDRP: a biological knowledge-driven approach for drug response prediction using multi-omics data in cancer cell lines.

BACKGROUND: Cancer heterogeneity results in patients with the same diagnosis responding differently to drugs, making treatments extremely challenging....

DeePedIMV: Deep learning model for early prediction of invasive mechanical ventilation in critically ill children.

BACKGROUND: Acute deterioration requiring invasive mechanical ventilation (IMV) is common in critically ill children and may arise from respiratory, c...

HGT-PepPI: A Heterogeneous Graph-Based Framework Leveraging Pragmatic Analysis for Peptide-Protein Interaction Prediction.

Peptide-Protein Interactions (PepPIs) are essential to a wide range of biological processes, including gene regulation, cellular homeostasis, and meta...

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts.

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resi...

Drug-likeness prioritised selection identifies anti-Escherichia coli candidates confirmed by molecular docking, dynamics simulations, and antibacterial assays.

To address the imbalance between antibacterial potency and developability in cephalosporin discovery against Escherichia coli, we developed a comprehe...

Illuminating the black box of traditional Chinese medicine: The pivotal role of transgenic fluorescent zebrafish.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) holds significant therapeutic potential, yet its modernization is hindered by the i...

The Effect of ChatGPT-Assisted Medication Dosage Calculation Training on Accuracy, Time, and Learning Satisfaction Among Nursing Students: A Quasi-Experimental Study.

Medication dosage calculation is a vital clinical skill essential for patient safety. However, many nursing students experience difficulties mastering...

Exploring pharmacy professionals insights for advancing the pharmacy curriculum: A qualitative study.

OBJECTIVE: To explore the gaps, needs, and priorities in the pharmacy curriculum of Pakistan and synthesize pharmacy professionals' perspectives to de...

Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in chronic disease management, including diabetes, where it has the potential to supp...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst growth and renal decline, is the leading genetic c...

Drug repurposing in oncology: Bridging computational discovery to clinical application.

Drug repurposing, the identification of new therapeutic applications for existing drugs, has emerged as a pragmatic and cost-efficient strategy to acc...