Results 91 to 100 of about 66,706 (243)

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

Advanced 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, Yiyu Gui, Guibo Luo, Yuchao Yang   +3 more
wiley   +1 more source

Thematic accuracy and completeness of topographic maps

, 2018
Väitekirja elektrooniline versioon ei sisalda ...
openaire   +1 more source

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

Advanced 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, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Can large language models be used to code text for thematic analysis? An explorative study

Discover Artificial Intelligence
In practice, thematic analysis of text involves six stages, among which text coding is particularly cognitively demanding, labor-intensive, and time-consuming. This study investigates and compares the potential of two large language models (LLMs), namely
Zhiyong Han, Aaron Tavasi, JuYoung Lee, Joshua Luzuriaga, Kevin Suresh, Michael Oppenheim, Fortunato Battaglia, Stanley R. Terlecky   +7 more
doaj   +1 more source

Opening Ottoman Miniature Collections Through Computational Access: Methodological Lessons for Digital Humanities

Journal of Open Humanities Data
Ottoman miniature collections represent a layered cultural heritage that combines artistic, historical, social, and intellectual dimensions. Yet, access to their content is often limited by catalogue records that provide only minimal descriptive ...
Esra Cansu Çan Beton, Zehra Taşkın
doaj   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jean‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Estimating forest canopy cover using Landsat7 ETM+ data [PDF]

تحقیقات جنگل و صنوبر ایران, 2005
The remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map ...
Khosro Mirakhorlou, Manoochehr Amani
doaj  

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

Advanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou, Qiang Gao, Liuchao Jin, Guoquan Xie, Kang Zhang, Wei‐Hsin Liao   +5 more
wiley   +1 more source

Frankenstein, thematic analysis and generative artificial intelligence: Quality appraisal methods and considerations for qualitative research.

PLoS ONE
ObjectiveTo determine accuracy and efficiency of using generative artificial intelligence (GenAI) to undertake thematic analysis.IntroductionWith the increasing use of GenAI in data analysis, testing the reliability and suitability of using GenAI to ...
Tanisha Jowsey, Peta Stapleton, Shawna Campbell, Alexandra Davidson, Cher McGillivray, Isabella Maugeri, Megan Lee, Justin Keogh   +7 more
doaj   +1 more source

Research on Thematic Risk Map Knowledge Recommendation from the Perspective of Public Security Prevention and Control

Redai dili
As a crucial visual aid for security information representation, thematic maps not only help public security management departments understand regional security conditions but also guide police deployment and patrol planning.
Shen Tianqi, Zheng Wen, Li Weihong
doaj   +1 more source