Exploring the Landscape of Explainable Artificial Intelligence (XAI): A Systematic Review of Techniques and Applications

Big Data and Cognitive Computing, Journal Year: 2024, Volume and Issue: 8(11), P. 149 - 149

Published: Oct. 31, 2024

Artificial intelligence (AI) encompasses the development of systems that perform tasks typically requiring human intelligence, such as reasoning and learning. Despite its widespread use, AI often raises trust issues due to opacity decision-making processes. This challenge has led explainable artificial (XAI), which aims enhance user understanding by providing clear explanations decisions paper reviews existing XAI research, focusing on application in healthcare sector, particularly medical medicinal contexts. Our analysis is organized around key properties XAI—understandability, comprehensibility, transparency, interpretability, explainability—providing a comprehensive overview techniques their practical implications.

Language: Английский

Towards clinical prediction with transparency: An explainable AI approach to survival modelling in residential aged care

Computer Methods and Programs in Biomedicine, Journal Year: 2025, Volume and Issue: 263, P. 108653 - 108653

Published: Feb. 15, 2025

Language: Английский