Prescriptions

Transformation of a Medical Information Department to Meet the New Healthcare Realities of the Post-Pandemic Era.

The role of Medical Information in the pharmaceutical industry is undergoing a profound transformation, driven by evolving stakeholder expectations, digital innovation, and the increasing complexity of therapeutic landscapes. Traditionally perceived as a reactive function focused on providing accurate and timely responses to healthcare professionals (HCPs), AstraZeneca's Medical Information depart...

Medical Spine Sagittal MRI Dataset for Segmentation and Foraminal Stenosis detection.

Lumbar spine disorders represent one of the most prevalent musculoskeletal conditions worldwide, particularly among the elderly population. Magnetic Resonance Imaging (MRI) is the gold-standard diagnostic tool due to its superior ability to visualize soft tissues, neural structures, and degenerative changes. However, accurate interpretation of lumbar MRI scans requires specialized clinical experti...

Subgroup identification of disparities in buprenorphine discontinuation in opioid-use disorder: A Virtual Twins machine learning approach using nationwide United States claims data, 2006-2022.

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This st...

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 opinio...

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. ...

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...

Impact of a personalized antidepressant prescription using genetics, socio-demographic and clinical data in major depressive disorder patients: A clinical study.

BACKGROUND: Major depressive disorder (MDD) is common and disabling, and antidepressant selection often follows a trial-and-error process. Predictix i...

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 ...