Results 141 to 150 of about 2,815,445 (292)
In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley +1 more source
This study, utilizing two large‐cohort datasets, employs interpretable neural networks. It demonstrates that incorporating brain morphology and functional and structural networks enhances predictive accuracy for general psychopathology and its dimensions.
Jing Xia, Nanguang Chen, Anqi Qiu
wiley +1 more source
Large Language Model‐Based Chatbots in Higher Education
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+4 more
wiley +1 more source
Image classification plays a pivotal role in biomedical image analysis. Herein, it is shown that large multimodal models, such as GPT‐4, achieve superior performance in one‐shot learning, generalization, interpretability, and text‐driven image classification. Applications span tissue, cell type, cellular state, and disease classification, outperforming
Wenpin Hou+4 more
wiley +1 more source
Applied Artificial Intelligence in Materials Science and Material Design
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel+7 more
wiley +1 more source
This study introduces a modular lab automation system with affordable robotics and artificial intelligence (AI), enabling flexible, human‐in‐the‐loop task orchestration. Key features include dynamic task recording, efficient data management, and AI‐assisted measurements.
Stefan Conrad+3 more
wiley +1 more source
The Use of Amphetamines for Improving Cognitive Impairment in Patients with Multiple Sclerosis [PDF]
Background: Multiple sclerosis (MS) is an autoimmune disorder that results in debilitating cognitive impairment in 40-65% of patients. There are no current treatments for this symptom of MS.
Kum, Hayley
core +1 more source
ChatMolData: A Multimodal Agent for Automatic Molecular Data Processing
While large language models (LLMs) struggle with molecular data due to single‐modality limitations, ChatMolData—a multimodal agent for processing databases, images, structure files, and documents—is presented. It combines LLMs with tools for retrieval, structuring, prediction, visualization, and search, achieving > 90% accuracy across 128 tasks.
Yi Yu+5 more
wiley +1 more source
R‐APEX is a knowledge graph platform developed to investigate how air pollutants such as particularly fine particulate matter (PM2.5) affect human health. By integrating large‐scale biomedical data and using machine learning, it reveals pollutant–gene–disease associations.
Zhixing Zhu+7 more
wiley +1 more source