Papers

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review.

Trends in the use of adult-specific preference-weighted health-related quality of life instruments in clinical trials over the past 50 years: a protocol for a meta-research study using deep learning-based natural language processing and large language models.

GARN3: A coarse-grained helix centered technique for RNA 3D structures prediction.

A multi-modal co-attention model for accurate drug-target interaction prediction.

Artificial Intelligence in Selected Domains of Drug Discovery: A Critical Narrative Review.

Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.

Comparison of local large language models for extraction of signs and symptoms data from electronic health records.

Research progress of artificial intelligence in high-throughput drug screening.

Artificial intelligence applications in automated dental report generation - a scoping review.

FourierDrug: a domain generalization framework for robust drug response prediction via frequency-space asymmetric attention.

Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms.

Causal effect estimation from trans-regulatory single-cell CRISPR screens.

Machine Learning-Based Prediction of Polymer Properties Using Structure-Property Relationship Modeling.

Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials.

Accuracy of Deep Learning Models in Detecting Mandibular Furcation Defects on Panoramic Radiographs.

In vitro profiling of Trypanosoma cruzi inhibitors identified from High throughput Screening and application to parasite painting.

Machine Learning in Non-fullerene Organic Solar Cells: Accelerating Discovery, Design, and Understanding.

How artificial intelligence is reshaping citation impact in oral and maxillofacial radiology journals: an 8-year analysis with editorial and clinical implications (JCR 2017-2024).

Machine Learning-Driven QSAR Modeling for pK<sub>a</sub> Prediction of Ionizable Lipids in Lipid Nanoparticles for Hepatic Gene Silencing.

Inferring the qualities of protein-RNA models with graph transformers.