Results 111 to 120 of about 64,270 (302)
The learning-oriented gamification virtual environments of Android Studio
Fátima Acnabel Valencia Castro +4 more
openalex +2 more sources
Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio +3 more
wiley +1 more source
His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li +13 more
wiley +1 more source
Quantitative Stain Mapping in X‐Ray Virtual Histology
Virtual histology promises 3D tissue examination without physical sectioning, yet has lacked the tissue‐specificity of conventional pathology. This work demonstrates the first quantitative three‐dimensional stain mapping at histologically relevant resolution, separating contrast agent from tissue to reveal cellular features such as nuclei. The approach
Dominik John +16 more
wiley +1 more source
The Role of Artificial Intelligence in Value Co-Creation in Virtual Learning Environments: The Moderating Role of Ethical Behavior [PDF]
Introduction: The aim of the present study was to investigate the role of artificial intelligence in value co-creation in virtual learning environments, with a focus on the moderating role of ethical behavior.
Emine Bolat +3 more
doaj
Multimodal Cross‐Attentive Graph‐Based Framework for Predicting In Vivo Endocrine Disruptors
A multimodal cross‐attentive graph neural network integrates molecular graphs with androgen and estrogen adverse outcome pathway (AOP)–anchored in vitro assay signals to predict in vivo endocrine disruption. By fusing information on Tier‐1 AOP logits with chemical structures, the framework achieves high accuracy and provides assay‐traceable ...
Eder Soares de Almeida Santos +6 more
wiley +1 more source
Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain‐Machine Interface
Episodic memory weaves together what, where, and when of experience into a personal narrative. Cutting‐edge AI models may decode this intricate process in real‐life settings, revealing how neural activity encodes naturalistic memories. By merging AI with brain–machine interfaces, researchers are edging closer to mapping and even engineering memory ...
Dong Song
wiley +1 more source
Renal fibrosis, a hallmark of CKD, lacks effective treatments. Herein, we developed a multimodal AI model (TCM‐SPred) to identify anti‐fibrotic agents and found that dehydrocostus lactone (DCL) targets IQGAP1 to inhibit Wnt signaling, blocking the interaction between IQGAP1 and CCT3, demonstrating potent anti‐fibrotic activity in vitro and in vivo ...
Weijiang Lin +12 more
wiley +1 more source

