Results 71 to 80 of about 23,034 (235)

Hydrogen Halide Gas Sensors: Active Materials, Operation Principles, and Emerging Technologies

Interdisciplinary Materials, EarlyView.
This review considers hydrogen halide (HX) gas sensors across functional materials and principles: acoustic, chemical, optical and nanophotonic. The strong acidity and reactivity of HX gases are discussed as constraints for stability and selectivity of these devices.
Xiuzhen Liu, Nikita Tukachev, Kehang Wang, Dmirty Zhirihin, Yaopeng Cheng, Pavel Krasnov, Mingzhao Song, Soslan Khubezhov, Wenping Yin, Emmanuel Stratakis, Sailing He, Andrey L. Rogach, Sergey Makarov   +12 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

Artificial intelligence strategies for predicting kinase inhibitor resistance: A comprehensive review of methods, challenges, and future perspectives

Journal of Intelligent Medicine, EarlyView.
Abstract Kinase inhibitors are essential in targeted cancer therapy, yet resistance often emerges through secondary mutations, activation of compensatory signaling pathways, or drug‐efflux mechanisms. Artificial intelligence (AI) provides a workflow‐based strategy rather than a list of unrelated tools for predicting and addressing kinase‐inhibitor ...
Faris Hassan, Mohanad Ali Deifallah, Alaa Zaghloul, Rania Elgohary   +3 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

Should Dermatologists Recommend Direct‐to‐Consumer App‐Based Remote Diagnostics? An Ethical Analysis

JEADV Clinical Practice, EarlyView.
ABSTRACT Background Dermatology patients still face barriers in accessing timely specialist care. As direct‐to‐consumer (DTC) apps for remote dermatological diagnostics proliferate, guidance is lacking. While promising efficiency and efficacy, their clinical—and ethical—legitimacy is not yet well established.
Sonja Mathes, Sebastian Seurig, Theresa Willem, Marta Dechant, Stephan Traidl, Mina Kang, Pedro Marques Pinto, Annette Binder, Tilo Biedermann, Ulf Darsow   +9 more
wiley   +1 more source

Effectiveness of Explainable Artificial Intelligence (XAI) Techniques for Improving Human Trust in Machine Learning Models: A Systematic Literature Review

IEEE Access
Most decision-making processes worldwide are increasingly relying on artificial intelligence (AI) algorithms to enhance human welfare. Explainable Artificial Intelligence (XAI) techniques are pivotal in addressing the bottlenecks of utilizing machine ...
In-On Wiratsin, Chaiyong Ragkhitwetsagul
doaj   +1 more source

Explainable Artificial Intelligence (XAI): A reason to believe?

Law in Context. A Socio-legal Journal, 2022
Artificial intelligence is an alluring technology which companies and governments hope to benefit from. In many circumstances a condition of its use is that humans can understand an explanation of why the action of an AI system took place. This has encouraged the development of a field of “explainable artificial intelligence”, or XAI.
openaire   +1 more source

3D Polymeric Nanonetworks: From Self‐Assembly to Advanced Fabrication

Macromolecular Materials and Engineering, EarlyView.
This review provides the first systematic cross‐method comparison of fabrication techniques for 3D polymeric nanonetworks. It evaluates five key strategies—block copolymer self‐assembly, hyper‐crosslinking, template‐assisted methods, 3D printing, and nanolithography—across critical metrics including resolution, throughput, scalability, and material ...
Carlos G. Cobos, Xiang Yan, Marisol Martín‐González   +2 more
wiley   +1 more source

Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review

BMJ Health & Care Informatics
Background Breast cancer is the most common disease in women. Recently, explainable artificial intelligence (XAI) approaches have been dedicated to investigate breast cancer. An overwhelming study has been done on XAI for breast cancer.
Worku Jimma, Daraje kaba Gurmessa
doaj   +1 more source

Explaining Explanations in AI [PDF]

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions.
Mittelstadt, Brent
core