Prescriptions

Expanding and Enhancing Neural Network-Based QM-AI Models for the Accurate Prediction of Halogen-π Interaction Energies in Protein Contexts.

In this study, we extend a previously introduced QM-AI strategy for predicting halogen···π interaction energies from a single aromatic model (representing phenylalanine) to multiple biologically relevant aromatic environments. Herein, neural network models were developed for halogen···π interactions involving phenol, imidazole, and indole, serving as model systems for the aromatic side chain resid...

Assessing ChatGPT's capability in understanding and reporting antiretroviral therapy drug-drug interactions (ACCURATE-DDI).

OBJECTIVES: Artificial intelligence tools are transforming access to medication information. However, their ability to accurately identify antiretroviral (ARV) drug-drug interactions (DDIs) remains unclear. This study evaluated ChatGPT's analysis of ARV-related DDIs compared to established HIV-specific DDI resources. DESIGN: Cross-sectional observational study. METHODS: Using ChatGPT4o-mini in Nov...

Evaluating the heterogeneous treatment effects of major depression polygenic risk scores on self-harm using causal forest.

BACKGROUND: Self-harm, defined as non-fatal self-inflicted harm regardless of suicidal intent, is a critical global health issue influenced by the int...

Emerging applications of large language models in ecology and conservation science.

Large language models (LLMs) mark a major development in artificial intelligence, with potentially transformative implications for ecology and conserv...

HopWD-DTA: a novel framework for drug-target affinity prediction fusing multi-hop neighborhoods and deep features.

CONTEXT: Accurate prediction of drug-target affinity (DTA) is crucial for accelerating drug discovery, but it remains a significant challenge. While d...

Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.

BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...

Conducting Medication Reviews: A Comparative Study Between ChatGPT-4 and Healthcare Professionals.

BACKGROUND: The increasing prevalence of patients with hyperpolypharmacy (> 10 medications) has made medication reviews increasingly complex. ChatGPT-...

Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.

Glioma is a highly malignant brain tumor with limited treatment options. We employed the Computational Analysis of Novel Drug Opportunities (CANDO) pl...

Development and validation of a precision treatment rules for first-line antipsychotic recommendations in first episode psychosis jointly incorporating effectiveness, side effects and patient preferences.

Selecting first-line antipsychotic medication for first episode of psychosis patients is a very challenging task requiring the clinicians to empirical...

Artificial intelligence at the frontlines: Emerging infectious and parasitic diseases in the digital era.

Emerging infectious diseases are one of the most significant threats to global health, driven by many factors such as zoonotic spillovers, climate cha...

DWPL-GCNMF: Structure-Aware Dynamic Weighted Pseudo-Label Learning for Adverse Drug Reaction Prediction.

Adverse drug reaction (ADR) prediction is typically formulated as drug-ADR association learning on extremely sparse, positive-unlabeled matrices, whic...

ChatGPT for obesity management: a review of evidence, potential challenges, and clinical implications.

The global rise in the prevalence of obesity highlights the need for accessible and effective solutions for obesity management. ChatGPT, one of the fa...

DrugBLIP: Exploring the Protein-Molecule Interaction Mechanisms with a Multi-task Learning Graph Transformer.

MOTIVATION: Traditional drug discovery methods are costly and inefficient, while existing deep learning approaches remain limited by task specificity ...

Differentiating long QT syndrome genotypes using electrocardiographic geometric parameterization and machine learning approaches.

Long QT Syndrome (LQTS) is an inherited cardiac disorder characterized by dysfunctional cardiac ion channels, which result in prolonged QT intervals o...

Code-Based Versus AutoML Methods for Pill Recognition in Clinical Settings: Comparative Performance Study.

BACKGROUND: Visual identification and verification of medications during dispensing and administration are prone to human error, particularly in high-...

Linear-Scaling and Memory-Efficient Implementation of van-der-Waals Interaction (DFT-D3) for Large Systems.

The van der Waals (vdW) interaction is ubiquitous in materials and is long-range by nature. To facilitate vdW-included atomic simulations in large sys...

Identifying treatment response classes to transcranial direct current stimulation (tDCS) from daily ecological momentary assessment (EMA) patterns in patients with depression.

IMPORTANCE: Transcranial direct current stimulation (tDCS) is known to be promising for depression, but heterogeneity across studies highlights the ne...

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, d...

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 R...

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...