Perspectives on the Influence of Pharmaceutical and MedTech Companies on Deprescribing Decisions and Conference Sponsorship: A Survey Study. [PDF]
Jungo KT +3 more
europepmc +1 more source
MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa +2 more
wiley +1 more source
Between principle and practice: a qualitative study of perceived relevance and impact of the Ethiopian national medical licensing examination. [PDF]
Belay LM +4 more
europepmc +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Comparison of the 2024 National Institute for Health and Care Excellence sepsis guideline for adults against the 2016 guidelines: a service evaluation. [PDF]
Bhattacharjee A, Bozorgi H, Boyle A.
europepmc +1 more source
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
Barriers to and enablers of prophylactic compression use by people at risk of venous leg ulcer recurrence: a qualitative study. [PDF]
Alkahtani AM +3 more
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Climate Change Denial as Identity Defence: Understanding Resistance Beyond Ignorance. [PDF]
Ebrahimi E.
europepmc +1 more source

