Results 141 to 150 of about 1,446 (247)

A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis

open access: yesAdvanced Intelligent Systems, EarlyView.
METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen   +3 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

Contact Force Estimation in Human–Robot Collaboration: A Case Study on Heavyweight Robotic Manipulators

open access: yesAdvanced Intelligent Systems, EarlyView.
The method presented in this paper provides a practical sensorless solution for estimating both contact force and contact location using only standard joint encoders and an available robot dynamic model. By reformulating the contact estimation problem using a single scalar equivalent contact parameter, the approach enables fast and robust computation ...
Thanh‐Quan Ta, Shyh‐Leh Chen
wiley   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

open access: yesAdvanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez   +3 more
wiley   +1 more source

Assessment of In Vitro Nano‐Cytotoxicity Through Fluorescence Microscopy via Neural Network‐Based Live/Dead Cell Classification

open access: yesAdvanced Intelligent Systems, EarlyView.
FluoAI is a two‐stage, label‐free method for quantifying nanomaterial‐induced cytotoxicity from conventional fluorescence microscopy images. Mask R‐CNN segmentation and DenseNet‐121 classification provide rapid live/dead classification matching human accuracy.
Ugur C. Topkiran   +6 more
wiley   +1 more source

Utility-Scale Quantum Computational Chemistry. [PDF]

open access: yesJ Phys Chem Lett
Castaldo D, Reiher M.
europepmc   +1 more source

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