Disaster Storylines and Knowledge Graphs from Global News with Large Language Models and Retrieval-Augmented Generation. [PDF]
Ronco M +7 more
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Ethical Imperatives for Retrieval-Augmented Generation in Clinical Nursing: Viewpoint on Responsible AI Use. [PDF]
Tu X, Shi C, Qian P, Wang L.
europepmc +1 more source
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Multi-Hardware Benchmarking of Open-Source Large Language Models with Retrieval-Augmented Generation for Mitsubishi FX-Series PLC Instruction List Code Generation. [PDF]
Yeh MF, Luo CC, Lu CL.
europepmc +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Advancing engineering research through context-aware and knowledge graph-based retrieval-augmented generation. [PDF]
Ghosh S, Mittal G.
europepmc +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
A temporally Anchored Retrieval-Augmented Generation Framework for Metabolic and Bariatric Surgery Patient Education: An IFSO Artificial Intelligence Task Force Multinational Validation Study. [PDF]
Atri YK +9 more
europepmc +1 more source

