Results 201 to 210 of about 47,624 (295)

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer   +3 more
wiley   +1 more source

A Steerable and Expandable Magnetic Aspiration Catheter for Enhanced Aspiration Thrombectomy

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents a novel magnetic aspiration catheter (MAC) that can be both actively steered and undergo distal‐end expansion via externally applied magnetic fields. The MAC facilitates precise branch selection and enhances clot engagement by improving endovascular navigation and aspiration efficiency. Phantom experiments validate its feasibility
Hakjoon Lee   +7 more
wiley   +1 more source

High‐Speed Altitude Regulation With Neuromorphic Camera and Lightweight Embedded Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Neuromorphic cameras deliver rapid, high‐dynamic‐range sensing but overwhelm embedded processors at high speeds. This work presents a lightweight, optimized Lucas–Kanade optical flow method with parallelization, gyroscopic derotation, and adaptive event slicing.
Simon L. Jeger   +3 more
wiley   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi   +5 more
wiley   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza   +2 more
wiley   +1 more source

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