Digital deception: Generative artificial intelligence in social engineering and phishing
Abstract The advancement of Artificial Intelligence (AI) and Machine Learning (ML) has
profound implications for both the utility and security of our digital interactions. This paper …
profound implications for both the utility and security of our digital interactions. This paper …
Artificial intelligence and explanation: How, why, and when to explain black boxes
Artificial intelligence (AI) is infiltrating nearly all fields of science by storm. One notorious
property that AI algorithms bring is their so-called black box character. In particular, they are …
property that AI algorithms bring is their so-called black box character. In particular, they are …
[HTML][HTML] Can physician judgment enhance model trustworthiness? A case study on predicting pathological lymph nodes in rectal cancer
K Kobayashi, Y Takamizawa, M Miyake, S Ito… - Artificial Intelligence in …, 2024 - Elsevier
Explainability is key to enhancing the trustworthiness of artificial intelligence in medicine.
However, there exists a significant gap between physicians' expectations for model …
However, there exists a significant gap between physicians' expectations for model …
The Accuracy and Faithfullness of AL-DLIME-Active Learning-Based Deterministic Local Interpretable Model-Agnostic Explanations: A Comparison with LIME and …
S Holm, L Macedo - World Conference on Explainable Artificial …, 2023 - Springer
The goal of this paper is twofold. Firstly, it aims to introduce a novel eXplainable Artificial
Intelligence (XAI) model, AL-DLIME (Active Learning-based Deterministic Local …
Intelligence (XAI) model, AL-DLIME (Active Learning-based Deterministic Local …
Nurses' perceptions of the design, implementation, and adoption of machine learning clinical decision support: A descriptive qualitative study
Introduction The purpose of this study was to explore nurses' perspectives on Machine
Learning Clinical Decision Support (ML CDS) design, development, implementation, and …
Learning Clinical Decision Support (ML CDS) design, development, implementation, and …
Identifying the severity of diabetic retinopathy by visual function measures using both traditional statistical methods and interpretable machine learning: a cross …
Aims/hypothesis To determine the extent to which diabetic retinopathy severity stage may be
classified using machine learning (ML) and commonly used clinical measures of visual …
classified using machine learning (ML) and commonly used clinical measures of visual …
Automating crisis communication in public institutions–Towards ethical conversational agents that support trust management
To improve disaster relief and crisis communication, public institutions (PIs) such as
administrations rely on automation and technology. As one example, the use of …
administrations rely on automation and technology. As one example, the use of …
Navigating the Integration of Machine Learning in Healthcare: Challenges, Strategies, and Ethical Considerations
S Ganesan, N Somasiri - Journal of Computational and Cognitive …, 2024 - ray.yorksj.ac.uk
The amalgamation of artificial intelligence (AI) and machine learning (ML) in healthcare
offers a revolutionary prospect to improve patient outcomes, optimize workflow, and curtail …
offers a revolutionary prospect to improve patient outcomes, optimize workflow, and curtail …
[LIVRE][B] The Future Circle of Healthcare
The Future Circle of Healthcare The Future Circle of Healthcare Sepehr Ehsani Patrick Glauner
Philipp Plugmann Florian M. Thieringer Editors AI, 3D Printing, Longevity, Ethics, and …
Philipp Plugmann Florian M. Thieringer Editors AI, 3D Printing, Longevity, Ethics, and …
Redesigning Relations: Coordinating Machine Learning Variables and Sociobuilt Contexts in COVID-19 and Beyond
H Howland, V Keyser, F Mahootian - The Future Circle of Healthcare: AI …, 2022 - Springer
We explore multi-scale relations in artificial intelligence (AI) use in order to identify difficulties
with coordinating relations between users, machine learning (ML) processes, and “sociobuilt …
with coordinating relations between users, machine learning (ML) processes, and “sociobuilt …