Results 151 to 160 of about 2,663,123 (277)

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
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, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Interacting Dimensions of Diversity: Cross-Categorization and the Functioning of Diverse Work Groups [PDF]

We conducted an experiment to show how the interplay between informational diversity and other dimensions of diversity can account for some of the inconsistent effects of informational diversity in previous research.
Dreu, C.K.W. de, Kleef, G.A. van, Knippenberg, D.L. van, Homan, A.C.   +3 more
core  

The impact of social interaction on abstract concepts. [PDF]

Psychon Bull Rev
Goriachun D, Mirault J, Ziegler JC, Strijkers K.   +3 more
europepmc   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

Advanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin, Seongho Lee, Seulchan Kim, Ho‐Il Ji, Joonhee Kang   +4 more
wiley   +1 more source

Post-saccadic disruption of semantic category information in naturalistic scenes. [PDF]

Cortex
Choi YM, Chiu TY, Golomb JD.
europepmc   +1 more source

U‐Net‐Based Prediction of Concealed Volume Loss in AZ31 From Optical Corrosion Imprints and As‐Exposed Surface Topography

Advanced Intelligent Discovery, EarlyView.
How much material loss is concealed beneath a layer of corrosion products? This proof‐of‐concept study demonstrates how concealed volume loss is inferred from the optical appearance and as‐exposed surface topography of AZ31 corrosion imprints. By predicting postcleaning depth maps, a multimodal U‐Net model estimates hidden volume loss without chromic ...
Lars Dammann, Ci Song, Bahram Vaghefinazari, Tim Würger, Anna Lisitsyna, Shadi Albarqouni, Mikhail L. Zheludkevich, Sviatlana V. Lamaka, Christian Feiler   +8 more
wiley   +1 more source

Physics‐Guided Modeling of Temperature‐Dependent Electrical Conductivity of Functional Oxides

Advanced Intelligent Discovery, EarlyView.
This complete workflow presents an automated, data‐driven screening of functional oxides based on their predicted electrical conductivity. A curated dataset is fed into TriCondNet, a charge‐transport, physics‐guided neural network that classifies an input composition's conduction mechanism and then simulates its conductivity–temperature profile.
Elias Assaad, Jae Evans, Troy D. Manning, Matthew J. Rosseinsky, Kerys Trathen, Bei Peng, Matthew S. Dyer   +6 more
wiley   +1 more source

Neural categorization of visual words of alphabetic and non-alphabetic languages. [PDF]

Elife
Zheng G, Han S.
europepmc   +1 more source

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source