Results 151 to 160 of about 20,583 (298)
(Dis)information Systems: a Systemic View of Disinformation
ABSTRACT Disinformation is an ancient social phenomenon that has found a favourable environment for dissemination in internet‐based social networks. While the scientific community seeks to address the problem by creating specific tools to detect and classify the various types of false information, we argue that systems thinking is necessary to ...
Herbert Laroca +2 more
wiley +1 more source
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study
Artificial intelligence (AI) systems substantially improve dermatologists’ diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing their confidence and trust in AI-driven decisions.
Tirtha Chanda +21 more
doaj +1 more source
High Nb (2.4 wt.%) addition to Maraging 300 steel drives lattice distortion and nanoscale Nb–Mo‐rich precipitation, confirmed by energy‐dispersive X‐ray spectroscopy mapping (Mo ~5.4 wt.%, Nb ~2.5 wt.%). Nanoindentation reveals strong matrix hardening (H >4.8 GPa) at 480°C aging, while 560°C induces ~1.92 vol.% reverted austenite, enabling tunable ...
Laylla Sharon B. Peixoto +9 more
wiley +1 more source
The goal of this study is to look at how the convergence of IoT and XAI (IoT-XAI) effects the explanation, prediction, and decision-making on customer perceived value (CPV) in SMEs, utilising CPV and IoT-XAI convergence theories.
Kwabena Abrokwah-Larbi
doaj +1 more source
Abstract Lightweight strain‐hardening ultra‐high‐performance concrete composite (SH‐UHPC) is an outstanding alternative for engineering applications and infrastructure thanks to its outstanding strength, toughness, ductility, and low density. The integration of artificial intelligence (AI)‐based modeling strategies into engineering problems can ...
Metin Katlav, Kazim Turk
wiley +1 more source
XAI In Fraud Detection: A Causal Perspective
Abstract Fraud detection systems powered by machine learning (ML) often lack transparency, raising concerns about trustworthiness and interpretability. While Explainable AI (XAI) addresses these issues, many methods rely on correlation rather than causation, potentially overlooking true fraud patterns.
Katiuscka van Veen +2 more
openaire +1 more source
Baseline Household Survey Results: Xai Xai District, Mozambique [PDF]
International Union for Conservation of Nature (IUCN) carried out household baseline survey in two sites in Mozambique in 2012/2013. This report presents the main results of the analysis of the survey carried out in November 2012 in seven villages, with ...
Dixon, R.
core
ABSTRACT Objective To provide an overview of potential biases resulting from the utilization of artificial intelligence (AI) in otolaryngology and techniques to mitigate them. Data Sources Literature review and expert opinion. Conclusions AI promises to fundamentally transform medicine.
Matthew T. Ryan, David A. Gudis
wiley +1 more source
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley +1 more source
Exploration and practice of XAI architecture
XAI(explainable AI) is an important component of trusted AI.In-depth research on the technology points of XAI has been carried out in the current industry, but systematic research on engineering implementation is lacking.This paper proposed a general XAI
Zhengxun XIA +6 more
doaj

