Papers Explainable artificial intelligence
“Explainable artificial intelligence” 태그가 달린 논문 971편 · 필터 해제
Explainable Artificial Intelligence in Biomedical Image Analysis: A Comprehensive Survey
Explainable artificial intelligence (XAI) has become increasingly important in biomedical image analysis to promote transparency, trust, and clinical adoption of DL models. While several surveys have reviewed XAI techniq…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)SurveyFrom Motion to Meaning: Biomechanics-Informed Neural Network for Explainable Cardiovascular Disease Identification
Cardiac diseases are among the leading causes of morbidity and mortality worldwide, which requires accurate and timely diagnostic strategies. In this study, we introduce an innovative approach that combines deep learning…
DiagnosticExplainable artificial intelligencefeature selectionImage RegistrationIXAII: An Interactive Explainable Artificial Intelligence Interface for Decision Support Systems
Although several post-hoc methods for explainable AI have been developed, most are static and neglect the user perspective, limiting their effectiveness for the target audience. In response, we developed the interactive …
Explainable artificial intelligenceTowards Transparent AI: A Survey on Explainable Large Language Models
Large Language Models (LLMs) have played a pivotal role in advancing Artificial Intelligence (AI). However, despite their achievements, LLMs often struggle to explain their decision-making processes, making them a 'black…
DecoderExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)SurveyTowards Interpretable and Efficient Feature Selection in Trajectory Datasets: A Taxonomic Approach
Trajectory analysis is not only about obtaining movement data, but it is also of paramount importance in understanding the pattern in which an object moves through space and time, as well as in predicting its next move. …
Explainable artificial intelligencefeature selectionCommunicating Smartly in the Molecular Domain: Neural Networks in the Internet of Bio-Nano Things
Recent developments in the Internet of Bio-Nano Things (IoBNT) are laying the groundwork for innovative applications across the healthcare sector. Nanodevices designed to operate within the body, managed remotely via the…
Dataset GenerationExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Toward the Explainability of Protein Language Models for Sequence Design
Transformer-based language models excel in a variety of protein-science tasks that range from structure prediction to the design of functional enzymes. However, these models operate as black boxes, and their underlying w…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Protein DesignWhen concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?
Concept-based explainable artificial intelligence (C-XAI) can help reveal the inner representations of AI models. Understanding these representations is particularly important in complex tasks like safety evaluation. Suc…
Explainable artificial intelligenceA Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
Despite promising developments in Explainable Artificial Intelligence, the practical value of XAI methods remains under-explored and insufficiently validated in real-world settings. Robust and context-aware evaluation is…
Explainable artificial intelligenceUnsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence
Risk stratification is a key tool in clinical decision-making, yet current approaches often fail to translate sophisticated survival analysis into actionable clinical criteria. We present a novel method for unsupervised …
Decision MakingExplainable artificial intelligenceSurvival AnalysisA Lightweight IDS for Early APT Detection Using a Novel Feature Selection Method
An Advanced Persistent Threat (APT) is a multistage, highly sophisticated, and covert form of cyber threat that gains unauthorized access to networks to either steal valuable data or disrupt the targeted network. These t…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)feature selectionIntrusion Detectionmidr: Learning from Black-Box Models by Maximum Interpretation Decomposition
The use of appropriate methods of Interpretable Machine Learning (IML) and eXplainable Artificial Intelligence (XAI) is essential for adopting black-box predictive models in fields where model and prediction explainabili…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Interpretable Machine LearningTransfer Learning and Explainable AI for Brain Tumor Classification: A Study Using MRI Data from Bangladesh
Brain tumors, regardless of being benign or malignant, pose considerable health risks, with malignant tumors being more perilous due to their swift and uncontrolled proliferation, resulting in malignancy. Timely identifi…
Brain Tumor ClassificationExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Transfer LearningDo Protein Transformers Have Biological Intelligence?
Deep neural networks, particularly Transformers, have been widely adopted for predicting the functional properties of proteins. In this work, we focus on exploring whether Protein Transformers can capture biological inte…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Applying XAI based unsupervised knowledge discovering for Operation modes in a WWTP. A real case: AQUAVALL WWTP
Water reuse is a key point when fresh water is a commodity in ever greater demand, but which is also becoming ever more available. Furthermore, the return of clean water to its natural environment is also mandatory. Ther…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
Recent explainable artificial intelligence (XAI) methods for time series primarily estimate point-wise attribution magnitudes, while overlooking the directional impact on predictions, leading to suboptimal identification…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Time SeriesRecent Advances in Medical Image Classification
Medical image classification is crucial for diagnosis and treatment, benefiting significantly from advancements in artificial intelligence. The paper reviews recent progress in the field, focusing on three levels of solu…
ClassificationExplainable artificial intelligenceimage-classificationImage Classification+1A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks
Over the past decade, Medical Image Segmentation (MIS) using Deep Neural Networks (DNNs) has achieved significant performance improvements and holds great promise for future developments. This paper presents a comprehens…
EthicsExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Image Segmentation+2Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100
Financial literacy is increasingly dependent on the ability to interpret complex financial data and utilize advanced forecasting tools. In this context, this study proposes a novel approach that combines transformer-base…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Interpretable Machine LearningStock Price Prediction+1DiCoFlex: Model-agnostic diverse counterfactuals with flexible control
Counterfactual explanations play a pivotal role in explainable artificial intelligence (XAI) by offering intuitive, human-understandable alternatives that elucidate machine learning model decisions. Despite their signifi…
counterfactualDecision MakingDiversityExplainable artificial intelligence+2