Prescriptions

Impact of generative AI interaction and output quality on university students' learning outcomes: a technology-mediated and motivation-driven approach.

This study investigates the influence of generative artificial intelligence (GAI) on university students' learning outcomes, employing a technology-mediated learning perspective. We developed and empirically tested an integrated model, grounded in interaction theory and technology-mediated learning theory, to examine the relationships between GAI interaction quality, GAI output quality, and learni...

MultiFG: integrating molecular fingerprints and graph embeddings via attention mechanisms for robust drug side effect prediction.

Accurate prediction of drug side effect frequencies is critical for drug safety assessment but remains challenging due to the high cost of clinical trials and the limited generalizability of existing models. We propose Multi Fingerprint and Graph Embedding model (MultiFG), a novel deep learning framework that integrates diverse molecular fingerprint types, graph-based embeddings, and similarity fe...

Beam orientation optimization in IMRT using sparse mixed integer programming and non-convex fluence map optimization.

Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, non-convex problem traditionally addressed with heur...

Accurate prediction of synergistic drug combination using a multi-source information fusion framework.

BACKGROUND: Accurately predicting synergistic drug combinations is critical for complex disease therapy. However, the vast search space of potential d...

Multi-modal Classification of Retinal Disease Based On Convolutional Neural Network.

Retinal diseases such as age-related macular degeneration and diabetic retinopathy will lead to irreversible blindness without timely diagnosis and tr...

Deep learning-based approach to third molar impaction analysis with clinical classifications.

This study developed a deep learning model for the automated detection and classification of impacted third molars using the Pell and Gregory Classifi...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a leading cause of death in the US. Urosepsis occur...

Drug-target interaction/affinity prediction: Deep learning models and advances review.

Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Food ...

Genetic features for drug responses in cancer - Investigating an ensemble-feature-selection approach.

Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an e...

LLM-DDI: Leveraging Large Language Models for Drug-Drug Interaction Prediction on Biomedical Knowledge Graph.

Drug-drug interaction (DDI) refers to the interaction relationships between drugs. Discovering new DDIs is crucial for advancing drug development and ...

An EEG-based seizure prediction model encoding brain network temporal dynamics.

EEG-based seizure prediction enables timely treatment for patients, but its performance is limited by the difficulty in effectively characterizing the...

Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations.

This study introduces a sophisticated predictive framework for determining drug solubility and activity values in formulations via machine learning. T...

Comparative analysis of model compression techniques for achieving carbon efficient AI.

The growing computational demands of models, such as BERT, have raised concerns about their environmental impact. This study addresses the pressing ne...

Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application.

A combined methodology was performed based on chemometrics and machine learning regressive models in estimation of polysaccharide-coated colonic drug ...

Classifying and diagnosing Alzheimer's disease with deep learning using 6735 brain MRI images.

Traditional diagnostic methods for Alzheimer's disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and...

Improved bio-inspired with machine learning computing approach for thyroid prediction.

Thyroid illness is widely recognised as a prevalent health condition that can result in a range of health disorders. Thyroid illnesses, namely hypothy...

Assessment of drug induced hyperuricemia and gout risk using the FDA adverse event reporting system.

Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also p...

Evaluation of large language models' ability to identify clinically relevant drug-drug interactions and generate high-quality clinical pharmacotherapy recommendations.

PURPOSE: Large language models (LLMs) are promising artificial intelligence (AI) tools to support clinical decision-making. The ability of LLMs to eva...

The Role of Precision Nutrition in Kidney Disease.

Precision nutrition utilizes an individualized approach in which dietary interventions are tailored according to patients' genetic, biologic, and envi...

Exploring the Acceptance and Opportunities of Using a Specific Generative AI Chatbot to Assist Parents in Managing Pediatric Rheumatological Chronic Health Conditions: Mixed Methods Study.

BACKGROUND: Health care chatbots can be used to support patients and their families with everyday decision-making. While there is some research on int...