Results 121 to 130 of about 2,085,409 (278)

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

SeXAI: Introducing Concepts into Black Boxes for Explainable Artificial Intelligence

, 2020
The interest in Explainable Artificial Intelligence (XAI) research is dramatically grown during the last few years. The main reason is the need of having systems that beyond being effective are also able to describe how a certain output has been obtained
Ivan Donadello, Mauro Dragoni
core  

DFT and Machine Learning Analysis of Eco‐Friendly Formamidinium Tin Iodide Perovskite Solar Cells: Optimizing Charge Transport Layers Through SCAPS‐1D Simulations

Energy Science &Engineering, EarlyView.
Machine learning using Random Forest, GB, XGBoost, and LightGBM regression algorithms: SHAP plot for PCE. ABSTRACT Tin‐based solar cells are the eco‐friendly alternative to the toxic lead‐based cells that are currently in use. In this context, Formamidinium Tin Iodide (FASnI3) emerges as a promising candidate due to its superior performance, exhibiting
Rabeya Khan, Md Rasidul Islam, I.K. Gusral Ghosh Apurba, Md. Amimul Ihsan, Rahat Ul Nasib, Mohammad Arefin, Md Rifatul Islam, Abu Zahid, Hasnain A. Ziad, Jehan Y. Al‐Humaidi   +9 more
wiley   +1 more source

Understanding the dilemma of explainable artificial intelligence: a proposal for a ritual dialog framework

Humanities & Social Sciences Communications
This paper addresses how people understand Explainable Artificial Intelligence (XAI) in three ways: contrastive, functional, and transparent. We discuss the unique aspects and challenges of each and emphasize improving current XAI understanding ...
Aorigele Bao, Yi Zeng
doaj   +1 more source

EXplainable Artificial Intelligence (XAI)—From Theory to Methods and Applications

IEEE Access
Intelligent applications supported by Machine Learning have achieved remarkable performance rates for a wide range of tasks in many domains. However, understanding why a trained algorithm makes a particular decision remains problematic. Given the growing
Evandro S. Ortigossa, Thales Gonçalves, L. Nonato   +2 more
semanticscholar   +1 more source

Study on the Helpfulness of Explainable Artificial Intelligence

294312Explainable Artificial Intelligence (XAI) is essential for building advanced machine learning-powered applications, especially in critical domains such as medical diagnostics or autonomous driving. Legal, business, and ethical requirements motivate
Kulicheva, Elizaveta, Von Klitzing, Julian, Melman, Xenia, Geißler, Christian, Labarta, Tobias, Froelian, Ronja   +5 more
core   +1 more source

Biosensors for Food Safety and Adulteration Monitoring: Applications, Smart Packaging Integration, and Pathways to Intelligent, Field‐Deployable Detection Systems

Food Safety and Health, EarlyView.
Biosensors enable rapid, sensitive, and portable detection of pathogens, contaminants, allergens, and food adulteration. Integration with smart packaging, smartphones, IoT, and machine learning supports real‐time monitoring and intelligent decision‐making, whereas microfluidics, biodegradable materials, explainable AI, and blockchain offer pathways ...
Mohima Akther Any, Abid Hassan Arnab, Liza Akter, Yusuf Chowdhury, Md. Hassan Bin Nabi, Md Abu Rayhan, Nazmul Islam, Wahidu Zzaman   +7 more
wiley   +1 more source

Transformative impact of explainable artificial intelligence: bridging complexity and trust

Discover Artificial Intelligence
Artificial Intelligence and Deep Learning have gained widespread popularity in all sectors and industries from healthcare to finance and industrial management.
Girish Paliwal, Ashish Kumar, Kanta Prasad Sharma, Deepshika Bhargava, Vijay Mohan Shrimal   +4 more
doaj   +1 more source

Citrus Essential Oils in Food Safety and Health: Advances in AI‐Assisted Authentication, Antimicrobial Applications, Sustainable Extraction, and Regulatory Translation

Food Safety and Health, EarlyView.
Citrus essential oils combine sustainable extraction, AI‐assisted authentication, multi‐omics profiling, antimicrobial activity, and regulatory safety to enhance food quality, detect adulteration, and promote consumer health, and support intelligent, sustainable food systems through innovative industrial applications and circular bioeconomy strategies.
Md. Hassan Bin Nabi, Liza Akter, Yusuf Chowdhury, Mohima Akther Any, Nazmul Islam, Erni Sofia Murtini, Nurul Huda, Wahidu Zzaman   +7 more
wiley   +1 more source

Mitigating Cognitive Biases in Predicting Student Dropout: Global and Local Explainability with Explainable Boosting Machine [PDF]

Journal of Universal Computer Science
This study explores the application of Explainable Artificial Intelligence (XAI) techniques to mitigate cognitive biases in predicting student dropout. Focusing on the Explainable Boosting Machine (EBM), we compare its performance and explainability with
Rodrigo Costa Camargos, Ismar Frango Silveira   +1 more
doaj   +3 more sources