Results 121 to 130 of about 24,617 (284)

Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

open access: yesWorld Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
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

Improving Tuberculosis Diagnosis using Explainable Artificial Intelligence in Medical Imaging

open access: yesJournal of Mathematical Sciences and Modelling
The integration of artificial intelligence (AI) applications in the healthcare sector is ushering in a significant transformation, particularly in developing more effective strategies for early diagnosis and treatment of contagious diseases like ...
Cem Özkurt
doaj   +1 more source

Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions

open access: yesWorld Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
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

A Probability‐Aware AI Framework for Reliable Anti‐Jamming Communication

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐hopping techniques. Nevertheless, these techniques become vulnerable when facing intelligent jammers.
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source

A Unified Fuzzy–Explainable AI Framework (FAS-XAI) for Customer Service Value Prediction and Strategic Decision-Making

open access: yesAI
Real-world decision-making often involves uncertainty, incomplete data, and the need to evaluate alternatives based on both quantitative and qualitative criteria.
Gabriel Marín Díaz
doaj   +1 more source

What if Adam Smith Debated an AI Economist: A Thought Experiment on Markets, Ethics, and the Invisible Hand

open access: yesBusiness Ethics, the Environment &Responsibility, EarlyView.
ABSTRACT Can AI‐driven capitalism sustain the moral preconditions of market order? We stage a dialogue between Adam Smith and a steel‐manned “EconAI” to test four Moral‐Market‐Fitness criteria: trustworthiness, fairness, non‐domination, and contestability, across 11 dilemmas.
Alexandra‐Codruța Bîzoi   +1 more
wiley   +1 more source

Open and Extensible Benchmark for Explainable Artificial Intelligence Methods

open access: yesAlgorithms
The interpretability requirement is one of the largest obstacles when deploying machine learning models in various practical fields. Methods of eXplainable Artificial Intelligence (XAI) address those issues.
Ilia Moiseev   +2 more
doaj   +1 more source

Unveiling the factors of aesthetic preferences with explainable AI

open access: yesBritish Journal of Psychology, EarlyView.
Abstract The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences.
Derya Soydaner, Johan Wagemans
wiley   +1 more source

Enhancing explainability in pacu fish image segmentation using saliency maps and combined explainable AI methods

open access: yesSmart Agricultural Technology
Advances in Artificial Intelligence (AI) have sparked concerns regarding the transparency of model outputs, necessitating the development of eXplainable Artificial Intelligence (XAI) techniques.
Juliana da C. Feitosa   +6 more
doaj   +1 more source

Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification

open access: yesBritish Journal of Psychology, EarlyView.
Abstract Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye‐tracking and compared their attention strategies ...
Ruoxi Qi   +4 more
wiley   +1 more source

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