Results 221 to 230 of about 2,302,430 (290)

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

open access: yesAdvanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi   +2 more
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik   +6 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

open access: yesAdvanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

Ultralow‐Power Floating‐Gate InGaZnO Content‐Addressable Memory for Wearable Electrocardiogram Anomaly Detection

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a subthreshold in‐memory anomaly detection architecture for wearable ECG monitoring using floating‐gate IGZO content‐addressable memories on a flexible substrate. Area‐engineered coupling provides a high subthreshold slope, while subthreshold operation realizes intrinsic exponential distance evaluation and linear voltage sensing ...
Hyung‐Jun Noh   +4 more
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

open access: yesAdvanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha   +2 more
wiley   +1 more source

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