Prescriptions

ATEdrug: A reliable human-in-the-loop annotation scheme for aspect term extraction and polarity detection in drug reviews.

Pharmacovigilance is vital for post-market drug safety monitoring. Traditional trials inadequately capture adverse reactions. Patient-generated opinions offer valuable insights but pose challenges due to limited availability, inefficient annotation scheme, and volume of drug reviews, indicating the need of automation. To address the challenge posed by the limited availability of annotated drug rev...

Artificial Intelligence in Personalized Breast Cancer Drug Safety: From Preclinical Toxicology to Clinical Risk Management.

PURPOSE: The artificial intelligence (AI) implementation in personalized medicine has transformed drug safety, especially in breast cancer treatment. The importance of the need to treat breast cancer individually is acute as the disorder is heterogeneous and reacts differently to the use of chemotherapeutic agents. METHODS: Use of AI technologies including machine learning algorithms, deep learnin...

Predicting Melanoma Impact on the Swedish Healthcare System from the Adult Population Using Machine Learning on Registry Data.

Melanoma incidence has increased in Western countries over the past 50 years, leading to significant healthcare costs. In Sweden, comprehensive health...

Health Prediction Using Hybrid Deep Learning Models: A Transparent and Interpretable Approach.

Obesity has become alarming globally, with mounting health emergencies related to a number of chronic conditions like cardiovascular disease, diabetes...

MVGF-DR: Multi-view Graph Feature Fusion Approach for Drug Repositioning.

Drug repositioning, exploring new indications for existing drugs, is emerging as a promising approach to accelerate drug discovery and reduce research...

EcoRxAgent: an AI agent for generating economically substitutable prescriptions.

The prescription is a critical bridge between medical diagnosis and therapeutic intervention, embodying a complex decision that balances medical evide...

SRMMP-CharQM, Physics-Informed Deep Learning for Toxicity Prediction: Quantum Mechanical Descriptors Enable Scaffold Hopping in Mitochondrial Membrane Potential Assays.

Disruption of mitochondrial membrane potential (SR-MMP, Stress Response─Mitochondrial Membrane Potential) is a critical toxicity end point in early dr...

AI-Assisted Dialysis Decision-Making: Assessing Agreement Between ChatGPT and Nephrologist in Initial Dialysis Indication and Prescription in Emergency and ICU Settings.

BACKGROUND Artificial intelligence (AI) is increasingly explored as a clinical decision-support tool in nephrology; however, its real-world applicabil...

CT-Free Quantitative Thyroid SPECT Based on Artificial Intelligence: A Prospective Multicenter Noninferiority Clinical Trial.

BACKGROUND: Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) is used for the differential diagnosis of thyrotoxicosi...

MAF-Net: Multimodal cross-attention-based fusion network for cardiovascular disease classification.

Cardiovascular disease ranks among the leading causes of death globally, posing a severe threat to human health. Consequently, rapid and accurate iden...

AI-derived therapeutic development of a serotonin receptor-targeting drug for the treatment of opioid use disorder.

The opioid epidemic has led to a devastating loss of life nationwide. Of those dependent on opioids, many individuals desire to quit or reduce use, bu...

Integrating generative AI and genetic causal inference identifies metformin as a repurposing candidate for normal tension glaucoma.

The normal tension glaucoma (NTG) has limited drug options since current antiglaucoma medications are mostly designed to decrease intraocular pressure...

Technology Matters: Emerging technologies in clinical informatics to support child and adolescent mental healthcare safety.

Electronic health records (EHRs) can support patient safety across medical settings but require thoughtful adaptation to serve specialty care. This ar...

Quantitative Coronary Atherosclerotic Plaque Burden From CCTA and the Benefit From Lipid-Lowering Medication.

BACKGROUND: We hypothesized that quantification of coronary atherosclerotic plaque burden by artificial intelligence-guided quantitative computed tomo...

An ethics-informed computable audit framework for monitoring misdiagnosis risk in AI-assisted diagnosis.

Diagnostic AI can misclassify under distribution shift and subgroup imbalance; governance signals are rarely computable at deploy time. We target depl...

Human Allele Frequency Distributions Contradict Current Narratives of Imminent Danger From Genetically Targeted Bioweapons.

Warnings of pathogens manufactured to target a specific ethnic group, so-called genetic bioweapons, have recently received considerable media attentio...

Development of a deep learning tool to detect drug-resistance epilepsy with EEG.

INTRODUCTION: Drug-resistant epilepsy affects about 30% of patients and is linked to poorer outcomes. Deep learning can extract complex patterns from ...

FCM vectorization for Twitter sentimental analysis using multi stacked BiLSTM.

Twitter data analysis gives valuable insights into various aspects of society, such as consumer opinions, political sentiments, brand reputation, and ...

Machine learning model for multi-factor risk prediction in airport construction under non-stop operations.

Airport construction under non-stop operations presents unique safety challenges due to complex multi-factor interactions that traditional qualitative...

An artificial intelligence model for accurate drug-target affinity prediction in medicinal chemistry.

Predicting Drug-Target Affinity (DTA) with high fidelity is critical for accelerating hit-to-lead optimization and understanding mechanism of action. ...