Prescriptions

Impact of an AI-powered hospital admission prediction dashboard to guide medication reconciliation in the emergency department: a retrospective before-after study.

INTRODUCTION: Medication reconciliation (MR) in the emergency department (ED) is essential to ensure medication safety, especially for patients admitted to the hospital. However, performing MR for all ED patients, including those discharged, can be inefficient. To optimize prioritization, an artificial intelligence (AI)-powered hospital admission prediction dashboard was introduced. AIM: The prima...

A computational framework for predicting drug-target interactions by fusing gene ontology information with cross attention.

MOTIVATION: Identifying drug-target interactions (DTIs) is a critical step in both drug discovery and drug repurposing. Accurate in silico prediction of DTIs can substantially reduce development time and costs. Recent advances in sequence-based methods have leveraged attention mechanisms to improve prediction accuracy. However, these approaches typically rely solely on the molecular structures of ...

NeuMTL: A Unified Multimodal Framework for Multi-Task Prediction in CNS Drug Discovery.

Deep learning has made significant progress in drug discovery. However, most existing models are single-task and single-modality, which not only limit...

Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index.

BACKGROUND AND OBJECTIVE: Relapse in Multiple Myeloma, driven by therapy-resistant cancer stem cells, necessitates the development of more specific an...

Transfer learning for non-invasive glucose prediction under albumin interference in NIR spectroscopy.

This study proposes a transfer learning framework for non-invasive glucose prediction using diffuse-reflectance near-infrared (NIR) spectroscopy, alon...

Evaluation of ADP Glucose Pyrophosphorylase Subunit Interaction in Wheat by Binding Free Energy Calculations.

ADP-glucose pyrophosphorylase (AGPase; E.C. 2.7.7.27) is the rate-limiting enzyme catalyzing the first committed step of starch biosynthesis in higher...

Efficient drug-target affinity prediction via interaction features and parallel CNN-BiLSTM with attention.

Drug-Target Affinity (DTA) prediction is critical for reducing failure rates in drug discovery, but existing deep learning methods often trade efficie...

Machine learning guided stimuli-responsive catheter for directional drug delivery and dynamic biliary state recognition.

Precise drug delivery in the biliary tract remains challenging due to the dynamic physiological environment and lack of control in existing systems. H...

Automating wound assessment: convolutional neural network-based mobile application for SINBAD classification system.

INTRODUCTION: Diabetic foot ulcer (DFU) assessment using the SINBAD system is essential for clinical decision-making but often limited by access to sp...

Representation meets optimization: Training PINNs and PIKANs for gray-box discovery in systems pharmacology.

Physics-Informed Kolmogorov-Arnold Networks (PIKANs) have been gaining attention as an effective counterpart to the original multilayer perceptron-bas...

Deep‑learning‑based detection of open‑apex teeth on panoramic radiographs using YOLO models.

OBJECTIVES: The use of deep learning in detecting teeth with open apices can prevent the need for additional radiographs for patients. The presented s...

Enhanced-performance flexible pressure sensors enabled by synergistic effect of hierarchical porous structures for motion sensing and deep learning-assisted speech recognition.

Amid the global wave of intelligentization, flexible pressure sensors have emerged as core sensing components owing to their excellent flexibility, po...

SSHF-DTI: Leveraging structural similarity and hierarchical features through a fusion network for drug-target interaction prediction.

Predicting drug-target interactions (DTI) and binding affinities (DTA) is essential for drug discovery, but experimental methods remain costly and tim...

Quality by Computational Design: Harnessing AI to Advance Rational Drug Development.

The pharmaceutical Quality by Design (QbD) principle aims to reduce risk and improve efficiency across drug development lifecycle. However, QbD was or...

BDM-YOLOv8n: A high-performance model for accurate fire detection in aerial imagery.

In recent years, UAV aerial imagery has emerged as a pivotal tool in fire detection. However, when capturing images at long distances, it will be affe...

Integrating AI-driven technologies and facial-semantic features for depression detection: A cross-sectional study.

BACKGROUND: Depression is a major global health concern, still individuals with depressive tendencies remain undetected in outpatient settings due to ...

Bayesian selection of lipidome dynamics features for a K-nearest neighbors (KNN) classifier model of tumor response in patients with advanced gastrointestinal adenocarcinoma undergoing systemic treatment.

BACKGROUND: Dysregulated lipid metabolism is common in patients with gastrointestinal (GI) cancer. This study investigated the ability of plasma lipid...

Arrhythmia risk predictions from molecular simulations of cardiac ion channel-drug interactions.

Unintended block of cardiac ion channels, particularly hERG (KV11.1), remains a key concern in drug development as disruption of ion channel function ...

Dosage adjustments in renal impairment among medical ward patients: ChatGPT® and DeepSeek® models' effectiveness in assessing those adjustments.

BACKGROUND: Due to altered drug clearance, renal impairment necessitates drug dose adjustments to prevent toxicity or therapeutic failure, yet inappro...

Synergistic impact of insulin resistance and hepatic fibrosis on cardiovascular events in patients with coronary artery disease: A machine learning subtyping and interaction analysis.

BACKGROUND AND AIMS: Insulin resistance (IR) and hepatic fibrosis are significant yet underexplored synergistic risk factors for cardiovascular events...