AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Efficacy and Safety of Ecopipam for Tourette Syndrome: A Phase 3 Randomized Clinical Trial.
Gilbert DL +11 more
europepmc +1 more source
Real-world switching and switch-back patterns among patients transitioning from adalimumab to biosimilars in the United States (February 2023 to August 2025). [PDF]
Gilbert Farrar K +4 more
europepmc +1 more source
Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha +2 more
wiley +1 more source
Long‑term outcomes after esophageal diversion: insights and implications. [PDF]
Alwatari Y +3 more
europepmc +1 more source
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed +15 more
wiley +1 more source
Evaluating the indirect interaction between glucagon-like peptide-1 receptor agonists and warfarin using real-world data. [PDF]
Gilbert SJ +5 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
Intraoperative diagnosis of a giant pedunculated uterine myoma mimicking an adnexal mass presenting with acute abdomen in a resource-limited setting. [PDF]
Achangwa C +3 more
europepmc +1 more source

